The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aer...The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles(QUAVs).This scheme mainly consists of predefinedtime estimators and fixed-time tracking controllers,with a hybrid Laplacian matrix describing the communication among these QUAVs.At the first layer,we devise predefined time estimators for leading and following QUAVs,enabling accurate estimation of desired information.In the second layer,we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator faults.Fixedtime translational tracking controllers are then proposed,and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking controllers.We employ an exact tracking differentiator to handle variables that are challenging to differentiate directly.The paper includes a demonstration of the control system stability through mathematical proof,as well as the presentation of simulation results and comparative simulations.展开更多
This paper presents a predefined-time controller for Multiple Space transportation Robots System (MSRS), which can be applied in on-orbit assembly tasks to transport modules to pre-assembly configuration quickly. Firs...This paper presents a predefined-time controller for Multiple Space transportation Robots System (MSRS), which can be applied in on-orbit assembly tasks to transport modules to pre-assembly configuration quickly. Firstly, to simplify the analysis and design of predefined-time controller, a Predefined-time Stability Criterion is proposed in the form of Composite Lyapunov Function (CLF-PSC). Besides simplicity, the CLF-PSC also has the advantage of less conservativeness due to utilization of initial state information. Secondly, a concept of Lp-Norm-Normalized Sign Function (LPNNSF) is proposed based on the CLF-PSC. Different from traditional norm-normalized sign function, the Lp-norm of LPNNSF can be selected arbitrarily according to practical control task requirements, which means that the proposed LPNNSF is more generalized and more convenient for calculation. Thirdly, a predefined-time disturbance observer and predefined-time controller are designed based on the LPNNSF. The observer has the property of predefined-time convergence to achieve quicker and more accurate estimation of the lumped disturbance. The controller has less control input and chattering phenomenon than traditional predefined-time controller. In addition, by introducing the observer into the controller, the closed-loop system enjoys high precision and strong robustness. Finally, the effectiveness of the proposed controller is verified by numerical simulations. By employing the controller, the MSRS can carry assembly modules to the desired pre-assembly configuration accurately within predefined time.展开更多
This paper develops a novel Neural Network(NN)-based adaptive nonsingular practical predefined-time controller for the hypersonic morphing aircraft subject to actuator faults. Firstly, a novel Lyapunov criterion of pr...This paper develops a novel Neural Network(NN)-based adaptive nonsingular practical predefined-time controller for the hypersonic morphing aircraft subject to actuator faults. Firstly, a novel Lyapunov criterion of practical predefined-time stability is established. Following the proposed criterion, a tangent function based nonsingular predefined-time sliding manifold and the control strategy are developed. Secondly, the radial basis function NN with a low-complexity adaptation mechanism is incorporated into the controller to tackle the actuator faults and uncertainties. Thirdly, rigorous theoretical proof reveals that the attitude tracking errors can converge to a small region around the origin within a predefined time, while all signals in the closed-loop system remain bounded. Finally, numerical simulation results are presented to verify the effectiveness and improved performance of the proposed control scheme.展开更多
The 110-mining method,a rising and revolutionary non-pillar longwall mining method,can obviously expand coal extraction ratio and minimize roadway incidents.However,in case of composite hard roof,problems such as diff...The 110-mining method,a rising and revolutionary non-pillar longwall mining method,can obviously expand coal extraction ratio and minimize roadway incidents.However,in case of composite hard roof,problems such as difficulty in commanding the entry steadiness and insufficient fragmentation and bulking of the goaf gangue are prevalent.In this study,a 110-mining method for roadway surrounding rock stability control technology based on a compensation mechanism was proposed.First,the composite hard roof cutting short cantilever beam(SCB)model was built and the compensation mechanism including stress and space dual compensation was studied.Subsequently,the controllable elements influencing the roadway steadiness were confirmed to consequently put forward a control technology based on stress compensation for entry support and space compensation for the fragmentation and bulking of goaf gangue.The control technology was finally verified through onsite engineering experiments in terms of composite hard roof.The adoption of the 110-mining method with compensation control technology indicated good support effect on the roadway.The initial and residual expansion coefficients of the goaf gangue increased by 0.6 and 0.6,respectively,and the maximum and average working resistances of the working face support decreased by 10.9%and 13.8%,respectively.Consequently,the deformations of reserved entry decreased,and entry steadiness was enhanced.The presented technique and effects got probably have practical values for non-pillar mining functions in comparable field.展开更多
The system performance of grid-connected photovoltaic(PV)has a serious impact on the grid stability.To improve the control performance and shorten the convergence time,a predefined-time controller based on backsteppin...The system performance of grid-connected photovoltaic(PV)has a serious impact on the grid stability.To improve the control performance and shorten the convergence time,a predefined-time controller based on backstepping technology and dynamic surface control is formulated for the inverter in the grid-connected photovoltaic.The time-varying tuning functions are introduced into state-tracking errors to realize the predefined-time control effect.To address the“computational explosion problem”in the design process of backstepping control,dynamic surface control is adopted to avoid the analytical calculations of virtual control.The disturbances of the PV system are estimated and compensated by adaptive laws.The control parameters are chosen and the global stability of the closed-loop is ensured by Lyapunov conditions.Simulation results confirm the effectiveness of the proposed controller and ensure the predefined time control in the photovoltaic inverter.展开更多
This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a termi...This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a terminal sliding mode is constructed.The upper bound of convergence time in the proposed scheme can be adjusted by the explicit parameters during the design process of the controller.In addition,it is proved that the attitude tracking error will converge within two periods of the preset time.These two periods are set between two ranges:From the initial values to the sliding mode surface and from the sliding mode surface to the region near the origin.Furthermore,an adaptive law is adopted to eliminate unknown external disturbances and the effects of the uncertainties in the quadrotor model,so it is unnecessary to require the prior knowledge of the upper bound of the perturbations.Simulation results are produced and comparative case studies are carried out to demonstrate that the proposed scheme has faster convergence speed and smaller tracking errors.展开更多
The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of trea...The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.展开更多
The Tethered Space Net Robot(TSNR)is an innovative solution for active space debris capture and removal.Its large envelope and simple capture method make it an attractive option for this task.However,capturing maneuve...The Tethered Space Net Robot(TSNR)is an innovative solution for active space debris capture and removal.Its large envelope and simple capture method make it an attractive option for this task.However,capturing maneuverable debris with the flexible and elastic underactuated net poses significant challenges.To address this,a novel formation control method for the TSNR is proposed through the integration of differential game theory and robust adaptive control in this paper.Specifically,the trajectory of the TSNR is obtained through the solution of a real-time feedback pursuit-evasion game with a dynamic target,where the primary condition is to ensure the stability of the TSNR.Furthermore,to minimize tracking errors and maintain a specific configuration,a robust adaptive formation control scheme with Artificial Potential Field(APF)based on a Finite-Time Convergent Extended State Observer(FTCESO)is investigated.The proposed control method has a key advantage in suppressing complex oscillations by a new adaptive law,thus precisely maintaining the configuration.Finally,numerical simulations are performed to demonstrate the effectiveness of the proposed scheme.展开更多
To address the challenge of achieving unified control across diverse nonlinear systems, a comprehensive control theory spanning from PID (Proportional-Integral-Derivative) to ACPID (Auto-Coupling PID) has been propose...To address the challenge of achieving unified control across diverse nonlinear systems, a comprehensive control theory spanning from PID (Proportional-Integral-Derivative) to ACPID (Auto-Coupling PID) has been proposed. The primary concept is to unify all intricate factors, including internal dynamics and external bounded disturbance, into a single total disturbance. This enables the mapping of various nonlinear systems onto a linear disturbance system. Based on the theory of PID control and the characteristic equation of a critically damping system, Zeng’s stabilization rules (ZSR) and an ACPID control force based on a single speed factor have been designed. ACPID control theory is both simple and practical, with significant scientific significance and application value in the field of control engineering.展开更多
When D:ξ→η is a linear ordinary differential (OD) or partial differential (PD) operator, a “direct problem” is to find the generating compatibility conditions (CC) in the form of an operator D<sub>1:</su...When D:ξ→η is a linear ordinary differential (OD) or partial differential (PD) operator, a “direct problem” is to find the generating compatibility conditions (CC) in the form of an operator D<sub>1:</sub>η→ξ such that Dξ = η implies D<sub>1</sub>η = 0. When D is involutive, the procedure provides successive first-order involutive operators D<sub>1</sub>,...,D<sub>n </sub>when the ground manifold has dimension n. Conversely, when D<sub>1</sub> is given, a much more difficult “inverse problem” is to look for an operator D:ξ→η having the generating CC D<sub>1</sub>η = 0. If this is possible, that is when the differential module defined by D<sub>1</sub> is “torsion-free”, that is when there does not exist any observable quantity which is a sum of derivatives of η that could be a solution of an autonomous OD or PD equation for itself, one shall say that the operator D<sub>1</sub> is parametrized by D. The parametrization is said to be “minimum” if the differential module defined by D does not contain a free differential submodule. The systematic use of the adjoint of a differential operator provides a constructive test with five steps using double differential duality. We prove and illustrate through many explicit examples the fact that a control system is controllable if and only if it can be parametrized. Accordingly, the controllability of any OD or PD control system is a “built in” property not depending on the choice of the input and output variables among the system variables. In the OD case and when D<sub>1</sub> is formally surjective, controllability just amounts to the formal injectivity of ad(D<sub>1</sub>), even in the variable coefficients case, a result still not acknowledged by the control community. Among other applications, the parametrization of the Cauchy stress operator in arbitrary dimension n has attracted many famous scientists (G. B. Airy in 1863 for n = 2, J. C. Maxwell in 1870, E. Beltrami in 1892 for n = 3, and A. Einstein in 1915 for n = 4). We prove that all these works are already explicitly using the self-adjoint Einstein operator, which cannot be parametrized and the comparison needs no comment. As a byproduct, they are all based on a confusion between the so-called div operator D<sub>2</sub> induced from the Bianchi operator and the Cauchy operator, adjoint of the Killing operator D which is parametrizing the Riemann operator D<sub>1</sub> for an arbitrary n. This purely mathematical result deeply questions the origin and existence of gravitational waves, both with the mathematical foundations of general relativity. As a matter of fact, this new framework provides a totally open domain of applications for computer algebra as the quoted test can be studied by means of Pommaret bases and related recent packages.展开更多
This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic mo...This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic model considering additional forces and moments resulting during the morphing process,and convert it into a Multiple Input Multiple Output(MIMO)virtual control system by importing virtual inputs.Secondly,a classical dynamics inversion controller is designed for the outer-loop system.A new Global Fast Terminal Incremental Sliding Mode Controller(NDO-GFTISMC)is proposed for the inner-loop system,in which an adaptive law is implemented to weaken control surface chattering,and a Nonlinear Disturbance Observer(NDO)is integrated to compensate for unknown disturbances.The whole control system is proven semiglobally uniformly ultimately bounded based on the multi-Lyapunov function method.Furthermore,we consider tracking errors and self-characteristics of actuators,a quadratic programmingbased dynamic control allocation law is designed,which allocates virtual control inputs to the asymmetrically deformed wingtip and rudder.Actuator dynamic models are incorporated to ensure physical realizability of designed allocation law.Finally,comparative experimental results validate the effectiveness of the designed control system and control allocation law.The NDO-GFTISMC features faster convergence,stronger robustness,and 81.25%and 75.0%reduction in maximum state tracking error under uncertainty compared to the Incremental Nonlinear Dynamic Inversion Controller based on NDO(NDO-INDI)and Incremental Sliding Mode Controller based on NDO(NDO-ISMC),respectively.The design of the morphing aircraft significantly enhances lateral maneuver capability,maintaining a substantial control margin during lateral maneuvering,reducing the burden of the rudder surface,and effectively solving the actuator saturation problem of traditional aircraft during lateral maneuvering.展开更多
Distributed adaptive predefined-time bipartite containment for a class of second-order nonlinear multi-agent systems are studied with actuator faults.The communication topology of multi-agent systems is fixed and dire...Distributed adaptive predefined-time bipartite containment for a class of second-order nonlinear multi-agent systems are studied with actuator faults.The communication topology of multi-agent systems is fixed and directed.To ensure that followers can reach the convex hull spanned by leaders under the conditions of actuator faults,the sliding mode method is introduced.Control protocol for multi-agent systems demonstrates its effectiveness.Finally,simulations are provided to verify the effectiveness of the proposed algorithm.展开更多
Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey.AO is applied in various applications and its numerous variants were proposed in the l...Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey.AO is applied in various applications and its numerous variants were proposed in the literature.However,chaos theory has not been extensively investigated in AO.Moreover,it is still not applied in the parameter estimation of electro-hydraulic systems.In this work,ten well-defined chaotic maps were integrated into a narrowed exploitation of AO for the development of a robust chaotic optimization technique.An extensive investigation of twenty-three mathematical benchmarks and ten IEEE Congress on Evolutionary Computation(CEC)functions shows that chaotic Aquila optimization techniques perform better than the baseline technique.The investigation is further conducted on parameter estimation of an electro-hydraulic control system,which is performed on various noise levels and shows that the proposed chaotic AO with Piecewise map(CAO6)achieves the best fitness values of and at noise levels and respectively.Friedman test 2.873E-05,1.014E-04,8.728E-031.300E-03,1.300E-02,1.300E-01,for repeated measures,computational analysis,and Taguchi test reflect the superiority of CAO6 against the state of the arts,demonstrating its potential for addressing various engineering optimization problems.However,the sensitivity to parameter tuning may limit its direct application to complex optimization scenarios.展开更多
A cable-driven redundant manipulator(CDRM)characterized by redundant degrees of freedom and a lightweight,slender design can perform tasks in confined and restricted spaces efficiently.However,the complex multistage c...A cable-driven redundant manipulator(CDRM)characterized by redundant degrees of freedom and a lightweight,slender design can perform tasks in confined and restricted spaces efficiently.However,the complex multistage coupling between drive cables and passive joints in CDRM leads to a challenging dynamic model with difficult parameter identification,complicating the efforts to achieve accurate modeling and control.To address these challenges,this paper proposes a dynamic modeling and adaptive control approach tailored for CDRM systems.A multilevel kinematic model of the cable-driven redundant manipulator is presented,and a screw theory is employed to represent the cable tension and cable contact forces as spatial wrenches,which are equivalently mapped to joint torque using the principle of virtual work.This approach simplifies the mapping process while maintaining the integrity of the dynamic model.A recursive method is used to compute cable tension section-by-section for enhancing the efficiency of inverse dynamics calculations and meeting the high-frequency demands of the controller,thereby avoiding large matrix operations.An adaptive control method is proposed building on this foundation,which involves the design of a dynamic parameter adaptive controller in the joint space to simplify the linearization process of the dynamic equations along with a closed-loop controller that incorporates motor parameters in the driving space.This approach improves the control accuracy and dynamic performance of the CDRM under dynamic uncertainties.The accuracy and computational efficiency of the dynamic model are validated through simulations,and the effectiveness of the proposed control method is demonstrated through control tests.This paper presents a dynamic modeling and adaptive control approach for CDRM to enhance accuracy and performance under dynamic uncertainties.展开更多
This paper introduces a lane-changing strategy aimed at trajectory planning and tracking control for intelligent vehicles navigating complex driving environments.A fifth-degree polynomial is employed to generate a set...This paper introduces a lane-changing strategy aimed at trajectory planning and tracking control for intelligent vehicles navigating complex driving environments.A fifth-degree polynomial is employed to generate a set of potential lane-changing trajectories in the Frenet coordinate system.These trajectories are evaluated using non-cooperative game theory,considering the interaction between the target vehicle and its surroundings.Models considering safety payoffs,speed payoffs,comfort payoffs,and aggressiveness are formulated to obtain a Nash equilibrium solution.This way,collision avoidance is ensured,and an optimal lane change trajectory is planned.Three game scenarios are discussed,and the optimal trajectories obtained are compared using the NGSIM dataset.Comparison of trajectory tracking effects by themodel predictive control(MPC)and linear quadratic regulator(LQR).Finally,the left lane change,right lane change,and abort lane change operations are verified in the autonomous driving simulation platform.Simulation and experimental results show that the strategy can plan appropriate lane change trajectory and accomplish tracking in complex environments.展开更多
Maintaining optimal quality of life(QoL)is a pivotal for“successful aging”.Understanding how the QoL of the elderly develops and what role psychological factors play in its development will help improve QoL from a p...Maintaining optimal quality of life(QoL)is a pivotal for“successful aging”.Understanding how the QoL of the elderly develops and what role psychological factors play in its development will help improve QoL from a psychological perspective.Embedded within the lifespan theory of control,this longitudinal study aimed to(1)map the temporal trajectory of QoL among Chinese older adults,(2)examine differential effects of tripartite negative emotions(stress,anxiety,depression),and(3)test themoderating role of control strategies(goal engagement,goal disengagement,self-protection)in emotion-QoL dynamics.A prospective cohort of 345 community-dwelling older adults(Mage=83.84±8.49 years;55.1%female)completed validated measures-SF-36 for QoL,DASS-21 for negative emotions,and an adapted Control Strategies Questionnaire(CAS)-at three waves spanning 12 months.Hierarchical linear modeling(HLM)with time-nested structure analyzed intraindividual changes and interindividual differences.QoL exhibited a significant linear decline over time(β=−4.75,p<0.001).Stress(β=−14.12,p<0.001)and anxiety(β=−11.24,p<0.001)robustly predicted QoL decline,whereas depression showed no significant effect.Control strategies had divergent associations:goal engagement(β=3.51,p<0.001)and self-protection(β=2.38,p=0.015)predicted higher baseline QoL,while goal disengagement accelerated decline(β=−7.00,p<0.001;interaction with time:β=−2.46,p<0.001).Contrary to hypotheses,control strategies did not moderate emotion-QoL associations(ΔR2=0.02,p=0.21).The results showed that stress and anxiety played an important role in the QoL of the elderly.At the same time,goal engagement and self-protection were beneficial to the QoL of the elderly,while goal disengagement was not conducive to QoL and its development among the elderly.Meanwhile,the negative effect of anxiety and stress on the QoL of the elderly was not affected by the control strategies.展开更多
Spillover of trypanosomiasis parasites from wildlife to domestic livestock and humans remains a major challenge world over.With the disease targeted for elimination by 2030,assessing the impact of control strategies i...Spillover of trypanosomiasis parasites from wildlife to domestic livestock and humans remains a major challenge world over.With the disease targeted for elimination by 2030,assessing the impact of control strategies in communities where there are human-cattle-wildlife interactions is therefore essential.A compartmental framework incorporating tsetse flies,humans,cattle,wildlife and various disease control strategies is developed and analyzed.The reproduction is derived and its sensitivity to different model parameters is investigated.Meanwhile,the optimal control theory is used to identify a combination of control strategies capable of minimizing the infected human and cattle population over time at minimal costs of implementation.The results indicates that tsetse fly mortality rate is strongly and negatively correlated to the reproduction number.It is also established that tsetse fly feeding rate in strongly and positively correlated to the reproduction number.Simulation results indicates that time dependent control strategies can significantly reduce the infections.Overall,the study shows that screening and treatment of humans may not lead to disease elimination.Combining this strategy with other strategies such as screening and treatment of cattle and vector control strategies will result in maximum reduction of tsetse fly population and disease elimination.展开更多
A mixed adaptive dynamic programming(ADP)scheme based on zero-sum game theory is developed to address optimal control problems of autonomous underwater vehicle(AUV)systems subject to disturbances and safe constraints....A mixed adaptive dynamic programming(ADP)scheme based on zero-sum game theory is developed to address optimal control problems of autonomous underwater vehicle(AUV)systems subject to disturbances and safe constraints.By combining prior dynamic knowledge and actual sampled data,the proposed approach effectively mitigates the defect caused by the inaccurate dynamic model and significantly improves the training speed of the ADP algorithm.Initially,the dataset is enriched with sufficient reference data collected based on a nominal model without considering modelling bias.Also,the control object interacts with the real environment and continuously gathers adequate sampled data in the dataset.To comprehensively leverage the advantages of model-based and model-free methods during training,an adaptive tuning factor is introduced based on the dataset that possesses model-referenced information and conforms to the distribution of the real-world environment,which balances the influence of model-based control law and data-driven policy gradient on the direction of policy improvement.As a result,the proposed approach accelerates the learning speed compared to data-driven methods,concurrently also enhancing the tracking performance in comparison to model-based control methods.Moreover,the optimal control problem under disturbances is formulated as a zero-sum game,and the actor-critic-disturbance framework is introduced to approximate the optimal control input,cost function,and disturbance policy,respectively.Furthermore,the convergence property of the proposed algorithm based on the value iteration method is analysed.Finally,an example of AUV path following based on the improved line-of-sight guidance is presented to demonstrate the effectiveness of the proposed method.展开更多
Congestion control is an inherent challenge of V2X(Vehicle to Everything)technologies.Due to the use of a broadcasting mechanism,channel congestion becomes severe with the increase in vehicle density.The researchers s...Congestion control is an inherent challenge of V2X(Vehicle to Everything)technologies.Due to the use of a broadcasting mechanism,channel congestion becomes severe with the increase in vehicle density.The researchers suggested reducing the frequency of packet dissemination to relieve congestion,which caused a rise in road driving risk.Obviously,high-risk vehicles should be able to send messages timely to alarm surrounding vehicles.Therefore,packet dissemination frequency should be set according to the corresponding vehicle’s risk level,which is hard to evaluate.In this paper,a two-stage fuzzy inference model is constructed to evaluate a vehicle’s risk level,while a congestion control algorithm DRG-DCC(Driving Risk Game-Distributed Congestion Control)is proposed.Moreover,HPSO is employed to find optimal solutions.The simulation results show that the proposed method adjusts the transmission frequency based on driving risk,effectively striking a balance between transmission delay and channel busy rate.展开更多
In order to increase the precision of flatness control, considering the principle and the measured data of rolling process essence, the theory-intelligent dynamic matrix model of flatness control is established by usi...In order to increase the precision of flatness control, considering the principle and the measured data of rolling process essence, the theory-intelligent dynamic matrix model of flatness control is established by using theory and in-telligent methods synthetically. The network model for rapidly calculating the theory effective matrix is established by the BP network optimized by the particle swarm algorithm. The network model for rapidly calculating the meas- urement effective matrix is established by the RBF network optimized by the cluster algorithm. The flatness control model can track the practical situation of roiling process by on-line selVlearning. The scheme for flatness control quantity calculation is established by combining the theory control matrix and the measurement control matrix. The simulation result indicates that the establishment of theory-intelligent dynamic matrix model of flatness control with stable control process and high precision supplies a new way and method for studying flatness on-line control model.展开更多
基金supported by Natural Science Basic Research Plan in Shaanxi Province of China(No.2023-JC-QN-0733)Guangdong Basic and Applied Basic Research Foundation,China(No.2022A1515110753)+2 种基金China Postdoctoral Science Foundation(No.2022M722583)China Industry-UniversityResearch Innovation Foundation(No.2022IT188)National Key Laboratory of Air-based Information Perception and Fusion and the Aeronautic Science Foundation of China(No.20220001068001)。
文摘The paper presents a two-layer,disturbance-resistant,and fault-tolerant affine formation maneuver control scheme that accomplishes the surrounding of a dynamic target with multiple underactuated Quadrotor Unmanned Aerial Vehicles(QUAVs).This scheme mainly consists of predefinedtime estimators and fixed-time tracking controllers,with a hybrid Laplacian matrix describing the communication among these QUAVs.At the first layer,we devise predefined time estimators for leading and following QUAVs,enabling accurate estimation of desired information.In the second layer,we initially devise a fixed-time hybrid observer to estimate unknown disturbances and actuator faults.Fixedtime translational tracking controllers are then proposed,and the intermediary control input from these controllers is used to extract the desired attitude and angular velocities for the fixed-time rotational tracking controllers.We employ an exact tracking differentiator to handle variables that are challenging to differentiate directly.The paper includes a demonstration of the control system stability through mathematical proof,as well as the presentation of simulation results and comparative simulations.
基金co-supported by the National Natural Science Foundation of China(Nos.12372048,12102343)the Key Program of the National Natural Science Foundation of China(No.U2013206)+1 种基金the China Postdoctoral Science Foundation(No.2023M742835)the Guangdong Basic and Applied Basic Research Foundation,China(No.2023A1515011421).
文摘This paper presents a predefined-time controller for Multiple Space transportation Robots System (MSRS), which can be applied in on-orbit assembly tasks to transport modules to pre-assembly configuration quickly. Firstly, to simplify the analysis and design of predefined-time controller, a Predefined-time Stability Criterion is proposed in the form of Composite Lyapunov Function (CLF-PSC). Besides simplicity, the CLF-PSC also has the advantage of less conservativeness due to utilization of initial state information. Secondly, a concept of Lp-Norm-Normalized Sign Function (LPNNSF) is proposed based on the CLF-PSC. Different from traditional norm-normalized sign function, the Lp-norm of LPNNSF can be selected arbitrarily according to practical control task requirements, which means that the proposed LPNNSF is more generalized and more convenient for calculation. Thirdly, a predefined-time disturbance observer and predefined-time controller are designed based on the LPNNSF. The observer has the property of predefined-time convergence to achieve quicker and more accurate estimation of the lumped disturbance. The controller has less control input and chattering phenomenon than traditional predefined-time controller. In addition, by introducing the observer into the controller, the closed-loop system enjoys high precision and strong robustness. Finally, the effectiveness of the proposed controller is verified by numerical simulations. By employing the controller, the MSRS can carry assembly modules to the desired pre-assembly configuration accurately within predefined time.
基金supported by the National Natural Science Foundation of China (Nos. 52233014, U2241215)。
文摘This paper develops a novel Neural Network(NN)-based adaptive nonsingular practical predefined-time controller for the hypersonic morphing aircraft subject to actuator faults. Firstly, a novel Lyapunov criterion of practical predefined-time stability is established. Following the proposed criterion, a tangent function based nonsingular predefined-time sliding manifold and the control strategy are developed. Secondly, the radial basis function NN with a low-complexity adaptation mechanism is incorporated into the controller to tackle the actuator faults and uncertainties. Thirdly, rigorous theoretical proof reveals that the attitude tracking errors can converge to a small region around the origin within a predefined time, while all signals in the closed-loop system remain bounded. Finally, numerical simulation results are presented to verify the effectiveness and improved performance of the proposed control scheme.
基金This work described herein was supported by the Program of China Scholarship Council(202206430008)the National Natural Science Foundation of China(NSFC)(52074300 and 52304111)+1 种基金the Yueqi Young Scholars Project of China University of Mining and Technology Beijing(2602021RC84)the Guizhou province science and technology planning project([2020]3007 and[2020]2Y019).
文摘The 110-mining method,a rising and revolutionary non-pillar longwall mining method,can obviously expand coal extraction ratio and minimize roadway incidents.However,in case of composite hard roof,problems such as difficulty in commanding the entry steadiness and insufficient fragmentation and bulking of the goaf gangue are prevalent.In this study,a 110-mining method for roadway surrounding rock stability control technology based on a compensation mechanism was proposed.First,the composite hard roof cutting short cantilever beam(SCB)model was built and the compensation mechanism including stress and space dual compensation was studied.Subsequently,the controllable elements influencing the roadway steadiness were confirmed to consequently put forward a control technology based on stress compensation for entry support and space compensation for the fragmentation and bulking of goaf gangue.The control technology was finally verified through onsite engineering experiments in terms of composite hard roof.The adoption of the 110-mining method with compensation control technology indicated good support effect on the roadway.The initial and residual expansion coefficients of the goaf gangue increased by 0.6 and 0.6,respectively,and the maximum and average working resistances of the working face support decreased by 10.9%and 13.8%,respectively.Consequently,the deformations of reserved entry decreased,and entry steadiness was enhanced.The presented technique and effects got probably have practical values for non-pillar mining functions in comparable field.
基金supported by the State Grid Corporation of China Headquarters Science and Technology Project under Grant No.5400-202122573A-0-5-SF。
文摘The system performance of grid-connected photovoltaic(PV)has a serious impact on the grid stability.To improve the control performance and shorten the convergence time,a predefined-time controller based on backstepping technology and dynamic surface control is formulated for the inverter in the grid-connected photovoltaic.The time-varying tuning functions are introduced into state-tracking errors to realize the predefined-time control effect.To address the“computational explosion problem”in the design process of backstepping control,dynamic surface control is adopted to avoid the analytical calculations of virtual control.The disturbances of the PV system are estimated and compensated by adaptive laws.The control parameters are chosen and the global stability of the closed-loop is ensured by Lyapunov conditions.Simulation results confirm the effectiveness of the proposed controller and ensure the predefined time control in the photovoltaic inverter.
文摘This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a terminal sliding mode is constructed.The upper bound of convergence time in the proposed scheme can be adjusted by the explicit parameters during the design process of the controller.In addition,it is proved that the attitude tracking error will converge within two periods of the preset time.These two periods are set between two ranges:From the initial values to the sliding mode surface and from the sliding mode surface to the region near the origin.Furthermore,an adaptive law is adopted to eliminate unknown external disturbances and the effects of the uncertainties in the quadrotor model,so it is unnecessary to require the prior knowledge of the upper bound of the perturbations.Simulation results are produced and comparative case studies are carried out to demonstrate that the proposed scheme has faster convergence speed and smaller tracking errors.
文摘The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.
基金supported by the National Natural Science Foundation of China(Nos.62222313,62173275,62327809,62303381,and 62303312)in part by the China Postdoctoral Science Foundation(No.2023M732225).
文摘The Tethered Space Net Robot(TSNR)is an innovative solution for active space debris capture and removal.Its large envelope and simple capture method make it an attractive option for this task.However,capturing maneuverable debris with the flexible and elastic underactuated net poses significant challenges.To address this,a novel formation control method for the TSNR is proposed through the integration of differential game theory and robust adaptive control in this paper.Specifically,the trajectory of the TSNR is obtained through the solution of a real-time feedback pursuit-evasion game with a dynamic target,where the primary condition is to ensure the stability of the TSNR.Furthermore,to minimize tracking errors and maintain a specific configuration,a robust adaptive formation control scheme with Artificial Potential Field(APF)based on a Finite-Time Convergent Extended State Observer(FTCESO)is investigated.The proposed control method has a key advantage in suppressing complex oscillations by a new adaptive law,thus precisely maintaining the configuration.Finally,numerical simulations are performed to demonstrate the effectiveness of the proposed scheme.
文摘To address the challenge of achieving unified control across diverse nonlinear systems, a comprehensive control theory spanning from PID (Proportional-Integral-Derivative) to ACPID (Auto-Coupling PID) has been proposed. The primary concept is to unify all intricate factors, including internal dynamics and external bounded disturbance, into a single total disturbance. This enables the mapping of various nonlinear systems onto a linear disturbance system. Based on the theory of PID control and the characteristic equation of a critically damping system, Zeng’s stabilization rules (ZSR) and an ACPID control force based on a single speed factor have been designed. ACPID control theory is both simple and practical, with significant scientific significance and application value in the field of control engineering.
文摘When D:ξ→η is a linear ordinary differential (OD) or partial differential (PD) operator, a “direct problem” is to find the generating compatibility conditions (CC) in the form of an operator D<sub>1:</sub>η→ξ such that Dξ = η implies D<sub>1</sub>η = 0. When D is involutive, the procedure provides successive first-order involutive operators D<sub>1</sub>,...,D<sub>n </sub>when the ground manifold has dimension n. Conversely, when D<sub>1</sub> is given, a much more difficult “inverse problem” is to look for an operator D:ξ→η having the generating CC D<sub>1</sub>η = 0. If this is possible, that is when the differential module defined by D<sub>1</sub> is “torsion-free”, that is when there does not exist any observable quantity which is a sum of derivatives of η that could be a solution of an autonomous OD or PD equation for itself, one shall say that the operator D<sub>1</sub> is parametrized by D. The parametrization is said to be “minimum” if the differential module defined by D does not contain a free differential submodule. The systematic use of the adjoint of a differential operator provides a constructive test with five steps using double differential duality. We prove and illustrate through many explicit examples the fact that a control system is controllable if and only if it can be parametrized. Accordingly, the controllability of any OD or PD control system is a “built in” property not depending on the choice of the input and output variables among the system variables. In the OD case and when D<sub>1</sub> is formally surjective, controllability just amounts to the formal injectivity of ad(D<sub>1</sub>), even in the variable coefficients case, a result still not acknowledged by the control community. Among other applications, the parametrization of the Cauchy stress operator in arbitrary dimension n has attracted many famous scientists (G. B. Airy in 1863 for n = 2, J. C. Maxwell in 1870, E. Beltrami in 1892 for n = 3, and A. Einstein in 1915 for n = 4). We prove that all these works are already explicitly using the self-adjoint Einstein operator, which cannot be parametrized and the comparison needs no comment. As a byproduct, they are all based on a confusion between the so-called div operator D<sub>2</sub> induced from the Bianchi operator and the Cauchy operator, adjoint of the Killing operator D which is parametrizing the Riemann operator D<sub>1</sub> for an arbitrary n. This purely mathematical result deeply questions the origin and existence of gravitational waves, both with the mathematical foundations of general relativity. As a matter of fact, this new framework provides a totally open domain of applications for computer algebra as the quoted test can be studied by means of Pommaret bases and related recent packages.
基金supported by the National Natural Science Foundation of China(Nos.62103052 and No.52175214)。
文摘This paper presents the design of an asymmetrically variable wingtip anhedral angles morphing aircraft,inspired by biomimetic mechanisms,to enhance lateral maneuver capability.Firstly,we establish a lateral dynamic model considering additional forces and moments resulting during the morphing process,and convert it into a Multiple Input Multiple Output(MIMO)virtual control system by importing virtual inputs.Secondly,a classical dynamics inversion controller is designed for the outer-loop system.A new Global Fast Terminal Incremental Sliding Mode Controller(NDO-GFTISMC)is proposed for the inner-loop system,in which an adaptive law is implemented to weaken control surface chattering,and a Nonlinear Disturbance Observer(NDO)is integrated to compensate for unknown disturbances.The whole control system is proven semiglobally uniformly ultimately bounded based on the multi-Lyapunov function method.Furthermore,we consider tracking errors and self-characteristics of actuators,a quadratic programmingbased dynamic control allocation law is designed,which allocates virtual control inputs to the asymmetrically deformed wingtip and rudder.Actuator dynamic models are incorporated to ensure physical realizability of designed allocation law.Finally,comparative experimental results validate the effectiveness of the designed control system and control allocation law.The NDO-GFTISMC features faster convergence,stronger robustness,and 81.25%and 75.0%reduction in maximum state tracking error under uncertainty compared to the Incremental Nonlinear Dynamic Inversion Controller based on NDO(NDO-INDI)and Incremental Sliding Mode Controller based on NDO(NDO-ISMC),respectively.The design of the morphing aircraft significantly enhances lateral maneuver capability,maintaining a substantial control margin during lateral maneuvering,reducing the burden of the rudder surface,and effectively solving the actuator saturation problem of traditional aircraft during lateral maneuvering.
基金2024 Jiangsu Province Youth Science and Technology Talent Support Project(funded by Yancheng Science and Technology Association)The 2024 Yancheng Key Research and Development Plan(Social Development)projects include“Research and Application of Multi-Agent Offline Distributed Trust Perception Virtual Wireless Sensor Network Algorithm”and“Research and Application of a New Type of Fishery Ship Safety Production Monitoring Equipment.”。
文摘Distributed adaptive predefined-time bipartite containment for a class of second-order nonlinear multi-agent systems are studied with actuator faults.The communication topology of multi-agent systems is fixed and directed.To ensure that followers can reach the convex hull spanned by leaders under the conditions of actuator faults,the sliding mode method is introduced.Control protocol for multi-agent systems demonstrates its effectiveness.Finally,simulations are provided to verify the effectiveness of the proposed algorithm.
基金funded by Taif University,Saudi Arabia,Project No.(TU-DSPP-2024-52).
文摘Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey.AO is applied in various applications and its numerous variants were proposed in the literature.However,chaos theory has not been extensively investigated in AO.Moreover,it is still not applied in the parameter estimation of electro-hydraulic systems.In this work,ten well-defined chaotic maps were integrated into a narrowed exploitation of AO for the development of a robust chaotic optimization technique.An extensive investigation of twenty-three mathematical benchmarks and ten IEEE Congress on Evolutionary Computation(CEC)functions shows that chaotic Aquila optimization techniques perform better than the baseline technique.The investigation is further conducted on parameter estimation of an electro-hydraulic control system,which is performed on various noise levels and shows that the proposed chaotic AO with Piecewise map(CAO6)achieves the best fitness values of and at noise levels and respectively.Friedman test 2.873E-05,1.014E-04,8.728E-031.300E-03,1.300E-02,1.300E-01,for repeated measures,computational analysis,and Taguchi test reflect the superiority of CAO6 against the state of the arts,demonstrating its potential for addressing various engineering optimization problems.However,the sensitivity to parameter tuning may limit its direct application to complex optimization scenarios.
基金Supported by National Natural Science Foundation of China(Grant No.52405040)Research Project of State Key Laboratory of Mechanical System and Vibration(Grant No.MSV202514)。
文摘A cable-driven redundant manipulator(CDRM)characterized by redundant degrees of freedom and a lightweight,slender design can perform tasks in confined and restricted spaces efficiently.However,the complex multistage coupling between drive cables and passive joints in CDRM leads to a challenging dynamic model with difficult parameter identification,complicating the efforts to achieve accurate modeling and control.To address these challenges,this paper proposes a dynamic modeling and adaptive control approach tailored for CDRM systems.A multilevel kinematic model of the cable-driven redundant manipulator is presented,and a screw theory is employed to represent the cable tension and cable contact forces as spatial wrenches,which are equivalently mapped to joint torque using the principle of virtual work.This approach simplifies the mapping process while maintaining the integrity of the dynamic model.A recursive method is used to compute cable tension section-by-section for enhancing the efficiency of inverse dynamics calculations and meeting the high-frequency demands of the controller,thereby avoiding large matrix operations.An adaptive control method is proposed building on this foundation,which involves the design of a dynamic parameter adaptive controller in the joint space to simplify the linearization process of the dynamic equations along with a closed-loop controller that incorporates motor parameters in the driving space.This approach improves the control accuracy and dynamic performance of the CDRM under dynamic uncertainties.The accuracy and computational efficiency of the dynamic model are validated through simulations,and the effectiveness of the proposed control method is demonstrated through control tests.This paper presents a dynamic modeling and adaptive control approach for CDRM to enhance accuracy and performance under dynamic uncertainties.
基金supported by the Science and Technology Program of Shandong Higher Education Institutions(Grant J18KA048).
文摘This paper introduces a lane-changing strategy aimed at trajectory planning and tracking control for intelligent vehicles navigating complex driving environments.A fifth-degree polynomial is employed to generate a set of potential lane-changing trajectories in the Frenet coordinate system.These trajectories are evaluated using non-cooperative game theory,considering the interaction between the target vehicle and its surroundings.Models considering safety payoffs,speed payoffs,comfort payoffs,and aggressiveness are formulated to obtain a Nash equilibrium solution.This way,collision avoidance is ensured,and an optimal lane change trajectory is planned.Three game scenarios are discussed,and the optimal trajectories obtained are compared using the NGSIM dataset.Comparison of trajectory tracking effects by themodel predictive control(MPC)and linear quadratic regulator(LQR).Finally,the left lane change,right lane change,and abort lane change operations are verified in the autonomous driving simulation platform.Simulation and experimental results show that the strategy can plan appropriate lane change trajectory and accomplish tracking in complex environments.
文摘Maintaining optimal quality of life(QoL)is a pivotal for“successful aging”.Understanding how the QoL of the elderly develops and what role psychological factors play in its development will help improve QoL from a psychological perspective.Embedded within the lifespan theory of control,this longitudinal study aimed to(1)map the temporal trajectory of QoL among Chinese older adults,(2)examine differential effects of tripartite negative emotions(stress,anxiety,depression),and(3)test themoderating role of control strategies(goal engagement,goal disengagement,self-protection)in emotion-QoL dynamics.A prospective cohort of 345 community-dwelling older adults(Mage=83.84±8.49 years;55.1%female)completed validated measures-SF-36 for QoL,DASS-21 for negative emotions,and an adapted Control Strategies Questionnaire(CAS)-at three waves spanning 12 months.Hierarchical linear modeling(HLM)with time-nested structure analyzed intraindividual changes and interindividual differences.QoL exhibited a significant linear decline over time(β=−4.75,p<0.001).Stress(β=−14.12,p<0.001)and anxiety(β=−11.24,p<0.001)robustly predicted QoL decline,whereas depression showed no significant effect.Control strategies had divergent associations:goal engagement(β=3.51,p<0.001)and self-protection(β=2.38,p=0.015)predicted higher baseline QoL,while goal disengagement accelerated decline(β=−7.00,p<0.001;interaction with time:β=−2.46,p<0.001).Contrary to hypotheses,control strategies did not moderate emotion-QoL associations(ΔR2=0.02,p=0.21).The results showed that stress and anxiety played an important role in the QoL of the elderly.At the same time,goal engagement and self-protection were beneficial to the QoL of the elderly,while goal disengagement was not conducive to QoL and its development among the elderly.Meanwhile,the negative effect of anxiety and stress on the QoL of the elderly was not affected by the control strategies.
文摘Spillover of trypanosomiasis parasites from wildlife to domestic livestock and humans remains a major challenge world over.With the disease targeted for elimination by 2030,assessing the impact of control strategies in communities where there are human-cattle-wildlife interactions is therefore essential.A compartmental framework incorporating tsetse flies,humans,cattle,wildlife and various disease control strategies is developed and analyzed.The reproduction is derived and its sensitivity to different model parameters is investigated.Meanwhile,the optimal control theory is used to identify a combination of control strategies capable of minimizing the infected human and cattle population over time at minimal costs of implementation.The results indicates that tsetse fly mortality rate is strongly and negatively correlated to the reproduction number.It is also established that tsetse fly feeding rate in strongly and positively correlated to the reproduction number.Simulation results indicates that time dependent control strategies can significantly reduce the infections.Overall,the study shows that screening and treatment of humans may not lead to disease elimination.Combining this strategy with other strategies such as screening and treatment of cattle and vector control strategies will result in maximum reduction of tsetse fly population and disease elimination.
基金National Key Research and Development Program of China,Grant/Award Number:2021YFC2801700Defense Industrial Technology Development Program,Grant/Award Numbers:JCKY2021110B024,JCKY2022110C072+6 种基金Science and Technology Innovation 2030-“New Generation Artificial Intelligence”Major Project,Grant/Award Number:2022ZD0116305Natural Science Foundation of Hefei,China,Grant/Award Number:202321National Natural Science Foundation of China,Grant/Award Numbers:U2013601,U20A20225Yangtze River Delta S&T Innovation Community Joint Research Project,Grant/Award Number:2022CSJGG0900Anhui Province Natural Science Funds for Distinguished Young Scholar,Grant/Award Number:2308085J02State Key Laboratory of Intelligent Green Vehicle and Mobility,Grant/Award Number:KFY2417State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle,Grant/Award Number:32215010。
文摘A mixed adaptive dynamic programming(ADP)scheme based on zero-sum game theory is developed to address optimal control problems of autonomous underwater vehicle(AUV)systems subject to disturbances and safe constraints.By combining prior dynamic knowledge and actual sampled data,the proposed approach effectively mitigates the defect caused by the inaccurate dynamic model and significantly improves the training speed of the ADP algorithm.Initially,the dataset is enriched with sufficient reference data collected based on a nominal model without considering modelling bias.Also,the control object interacts with the real environment and continuously gathers adequate sampled data in the dataset.To comprehensively leverage the advantages of model-based and model-free methods during training,an adaptive tuning factor is introduced based on the dataset that possesses model-referenced information and conforms to the distribution of the real-world environment,which balances the influence of model-based control law and data-driven policy gradient on the direction of policy improvement.As a result,the proposed approach accelerates the learning speed compared to data-driven methods,concurrently also enhancing the tracking performance in comparison to model-based control methods.Moreover,the optimal control problem under disturbances is formulated as a zero-sum game,and the actor-critic-disturbance framework is introduced to approximate the optimal control input,cost function,and disturbance policy,respectively.Furthermore,the convergence property of the proposed algorithm based on the value iteration method is analysed.Finally,an example of AUV path following based on the improved line-of-sight guidance is presented to demonstrate the effectiveness of the proposed method.
基金supported by the special key project of Chongqing Technology Innovation and Application Development under Grant No.cstc2021jscx-gksbX0057the Special Major Project of Chongqing Technology Innovation and Application Development under Grant No.CSTB2022TIADSTX0003.
文摘Congestion control is an inherent challenge of V2X(Vehicle to Everything)technologies.Due to the use of a broadcasting mechanism,channel congestion becomes severe with the increase in vehicle density.The researchers suggested reducing the frequency of packet dissemination to relieve congestion,which caused a rise in road driving risk.Obviously,high-risk vehicles should be able to send messages timely to alarm surrounding vehicles.Therefore,packet dissemination frequency should be set according to the corresponding vehicle’s risk level,which is hard to evaluate.In this paper,a two-stage fuzzy inference model is constructed to evaluate a vehicle’s risk level,while a congestion control algorithm DRG-DCC(Driving Risk Game-Distributed Congestion Control)is proposed.Moreover,HPSO is employed to find optimal solutions.The simulation results show that the proposed method adjusts the transmission frequency based on driving risk,effectively striking a balance between transmission delay and channel busy rate.
基金Item Sponsored by National High-Tech Research and Development Project of China(2009AA04Z143)Natural Science Foundation of Hebei Province of China(E2006001038)Hebei Provincial Science and Technology Project of China(10212101D)
文摘In order to increase the precision of flatness control, considering the principle and the measured data of rolling process essence, the theory-intelligent dynamic matrix model of flatness control is established by using theory and in-telligent methods synthetically. The network model for rapidly calculating the theory effective matrix is established by the BP network optimized by the particle swarm algorithm. The network model for rapidly calculating the meas- urement effective matrix is established by the RBF network optimized by the cluster algorithm. The flatness control model can track the practical situation of roiling process by on-line selVlearning. The scheme for flatness control quantity calculation is established by combining the theory control matrix and the measurement control matrix. The simulation result indicates that the establishment of theory-intelligent dynamic matrix model of flatness control with stable control process and high precision supplies a new way and method for studying flatness on-line control model.
