Considering that actual systems are often constrained by multiple factors such as state limitation,actuator saturation and actuator failure at the same time,this paper provides an effective solution for non-affine mul...Considering that actual systems are often constrained by multiple factors such as state limitation,actuator saturation and actuator failure at the same time,this paper provides an effective solution for non-affine multi-player systems,which can guarantee the required performance while saving communication cost.Initially,an auxiliary system is established to accommodate state limitations,following which the controller design is partitioned into two distinct segments,addressing different types of faults.Specifically,the discontinuous and continuous aspects of the controller are achieved by sliding-mode control(SMC)and adaptive critic design(ACD),respectively.During the implementation of ACD to solve the guaranteed value function incorporating the utility function designed for the asymmetric saturation of the control input,two adaptive schemes including adaptive eventtriggered impulsive control(AETIC)and adaptive self-triggered impulsive control(ASTIC)are introduced successively.It is proved that the system maintains exponential stability rather than asymptotic stability and the state signals keep ultimately uniformly bounded(UUB).Finally,the effectiveness of the proposed control sequence is verified by simulation comparisons.展开更多
This article presents an adaptive fault-tolerant tracking control strategy for unknown affine nonlinear systems subject to actuator faults and external disturbances.To address the hyperparameter initialization challen...This article presents an adaptive fault-tolerant tracking control strategy for unknown affine nonlinear systems subject to actuator faults and external disturbances.To address the hyperparameter initialization challenges inherent in conventional neural network training,an improved self-organizing radial basis function neural network(SRBFNN)with an input-dependent variable structure is developed.Furthermore,a novel selforganizing RBFNN-based observer is introduced to estimate system states across all dimensions.Leveraging the reconstructed states,the proposed adaptive controller effectively compensates for all uncertainties,including estimation errors in the observer,ensuring accurate state tracking with reduced control effort.The uniform ultimate boundedness of all closed-loop signals and tracking errors is rigorously established via Lyapunov stability analysis.Finally,simulations on two different nonlinear systems comprehensively validate the effectiveness and superiority of the proposed control approach.展开更多
A direct self-repairing control approach is proposed for helicopter via quantum control techniques and adaptive compensator when some complex faults occur. For a linear varying-parameter helicopter control system, the...A direct self-repairing control approach is proposed for helicopter via quantum control techniques and adaptive compensator when some complex faults occur. For a linear varying-parameter helicopter control system, the model reference adaptive control law is designed and an adaptive compensator is used for improving its self-re- pairing capability. To enhance anti-interference capability of helicopter, quantum control feedforward is added be- tween fault and disturbance. Simulation results illustrate the effectiveness and feasibility of the approach.展开更多
With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided b...With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided by synchronous generators.To address this critical issue,Virtual Synchronous Generator(VSG)technology has emerged as a highly promising solution by emulating the inertia and damping characteristics of conventional synchronous generators.To enhance the operational efficiency of virtual synchronous generators(VSGs),this study employs smallsignal modeling analysis,root locus methods,and synchronous generator power-angle characteristic analysis to comprehensively evaluate how virtual inertia and damping coefficients affect frequency stability and power output during transient processes.Based on these analyses,an adaptive control strategy is proposed:increasing the virtual inertia when the rotor angular velocity undergoes rapid changes,while strengthening the damping coefficient when the speed deviation exceeds a certain threshold to suppress angular velocity oscillations.To validate the effectiveness of the proposed method,a grid-connected VSG simulation platform was developed inMATLAB/Simulink.Comparative simulations demonstrate that the proposed adaptive control strategy outperforms conventional VSGmethods by significantly reducing grid frequency deviations and shortening active power response time during active power command changes and load disturbances.This approach enhances microgrid stability and dynamic performance,confirming its viability for renewable-dominant power systems.Future work should focus on experimental validation and real-world parameter optimization,while further exploring the strategy’s effectiveness in improvingVSG low-voltage ride-through(LVRT)capability and power-sharing applications in multi-parallel configurations.展开更多
This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Ham...This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Hamiltonian principle.An analysis of internal flow’s influence on the vibration characteristics of flexible marine risers is conducted.Then,for the uncertain environmental disturbance,the adaptive fuzzy logic system is introduced to dynamically approximate the boundary disturbance,and a robust adaptive fuzzy boundary control is proposed.The uniform boundedness of the closed-loop system is proved based on Lyapunov theory.The well-posedness of the closed-loop system is proved by operator semigroup theory.The proposed control’s effectiveness is validated through comparison with existing control methods.展开更多
This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-tri...This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.展开更多
The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To addre...The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To address the versatile thrust demand under complex dynamic characteristics of the adaptive cycle engine,this paper proposes a direct thrust estimation and control method based on the Model-Free Adaptive Control(MFAC)algorithm.First,an improved Sliding Mode Control-MFAC(SMC-MFAC)algorithm has been developed by introducing a sliding mode variable structure into the standard Full Format Dynamic Linearization-MFAC(FFDL-MFAC)and designing self-adaptive weight coefficients.Then a trivariate double-loop direct thrust control structure with a controller-based thrust estimator and an outer command compensation loop has been established.Through thrust feedback and command correction,accurate control under multi-mode and operation conditions is achieved.The main contribution of this paper is the improved algorithm that combines the tracking capability of the MFAC and the robustness of the SMC,thus enhancing the dynamic performance.Considering the requirements of the online thrust feedback,the designed MFAC-based thrust estimator significantly speeds up the calculation.Additionally,the proposed command correction module can achieve the adaptive thrust control without affecting the operation of the inner loop.Simulations and Hardware-in-Loop(HIL)experiments have been performed on an adaptive cycle engine component-level model to investigate the estimation and control effect under different modes and health conditions.The results demonstrate that both the thrust estimation precision and operation speed are significantly improved compared with Extended Kalman Filter(EKF).Furthermore,the system can accelerate the response of the controlled plant,reduce the overshoot,and realize the thrust recovery within the safety range when the engine encounters the degradation.展开更多
This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an a...This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an auxiliary system is established.Based on the finite-time stability theory and inverse optimal theory,a fuzzy adaptive inverse finite-time inverse optimal control method is proposed.It is proven that the formulated control approach guarantees the stability of the controlled systems,while ensuring that errors converge to a small neighborhood of zero within finite time.Moreover,the optimized control performance can be achieved.Eventually,the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.展开更多
This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling m...This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling matrices to be symmetric or irreducible.We have the advantages of using adaptive control method to reduce control gain and pinning control technology to reduce cost.By con-structing Lyapunov function,some sufficient synchronization criteria are established.Finally,numerical examples are employed to illustrate the effectiveness of the proposed approach.展开更多
In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of ...In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of pneumatic systems can significantly impact the force control accuracy of pneumatic polishing system end-effectors.To enhance responsiveness and control precision during the flexible polishing process,this study proposes an observer-based fuzzy adaptive control(OBFAC)scheme.To ensure control accuracy under an uncertain dynamic contact model,a fuzzy state observer is designed to estimate unmeasured states,while fuzzy logic approximates the uncertain nonlinear functions in the model to improve control performance.Additionally,the integral barrier Lyapunov function is employed to ensure that all states remain within predefined constraints.The stability of the proposed control scheme is analyzed using the Lyapunov function,and a pneumatic polishing experimental platform is constructed to conduct polishing contact force control experiments under multiple scenarios.Experimental results demonstrate that the proposed OBFAC scheme achieves superior tracking control performance compared to existing control schemes.展开更多
This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are de...This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are described.The adaptive optimal control law consists of the sum of the optimal control component and the adaptive control component.First,the optimal control law is designed for the model of the suspension system after ignoring the components of uncertain parameters and exogenous disturbance caused by the road surface.The optimal control law expresses the desired dynamic characteristics of the suspension system.Next,the adaptive component is designed with the purpose of compensating for the effects caused by uncertain parameters and exogenous disturbance caused by the road surface;the adaptive component has adaptive parameter rules to estimate uncertain parameters and exogenous disturbance.When exogenous disturbances are eliminated,the system responds with an optimal controller designed.By separating theoretically the dynamic of a semi-active suspension system,this solution allows the design of two separate controllers easily and has reduced the computational burden and the use of too many tools,thus allowing for more convenient hardware implementation.The simulation results also show the effectiveness of damping oscillations of the proposed solution in this article.展开更多
Tracking control of tendon-driven manipulators has become a prevalent research area.However,the existence of flexible elastic tendons generates substantial residual vibrations,resulting in difficulties for trajectory ...Tracking control of tendon-driven manipulators has become a prevalent research area.However,the existence of flexible elastic tendons generates substantial residual vibrations,resulting in difficulties for trajectory tracking control of the manipulator.This paper proposes the radial basis function neural network adaptive hierarchical sliding mode control(RBFNNA-HSMC)method,which combines the dynamic model of the elastic tendon-driven manipulator(ETDM)with radial basis neural network adaptive control and hierarchical sliding mode control technology.The aim is to achieve trajectory tracking control of ETDM even under conditions of model inaccuracy and disturbance.The Lyapunov stability theory demonstrates the stability of the proposed RBFNNA-HSM controller.In order to assess the effectiveness and adaptability of the proposed control method,simulations and experiments were performed on a two-DOF ETDM.The RBFNNA-HSM method shows superior tracking accuracy compared to traditional modelbased HSM control.The experiment shows that the maximum tracking error for ETDM double-joint trajectory tracking is below 2.593×10-3rad and 1.624×10-3rad,respectively.展开更多
Sliding mode control(SMC)is a well-known robust nonlinear control method with strong robustness and fast response which has been widely used in many applications.This paper introduces the major results of SMC design m...Sliding mode control(SMC)is a well-known robust nonlinear control method with strong robustness and fast response which has been widely used in many applications.This paper introduces the major results of SMC design methods that the authors have achieved in the last decade.Undoubtedly,our results are obtained based on many other researchers'pioneer work in the literature which will not be discussed in detail here.Notably,our development has a main focus on tackling practical issues such that a proposed or enhanced SMC approach is effectively applicable to motion control systems.Issues on sliding function and adaptive gain designs in SMC and their control features will be both discussed in this paper.Those issues comprise fast convergent speed,predefined convergent time,input saturation restriction,chattering reduction,and unknown disturbance suppression.Lastly,conclusion and a few remarks on future research directions are presented.展开更多
In this study,we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults.First,an inverse hysteresis dynamics model is introduced,and then...In this study,we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults.First,an inverse hysteresis dynamics model is introduced,and then the control input is divided into an expected input and an error compensator.Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis.Subsequently,by modifying the adaptive laws and local control laws,a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system.Through the direct Lyapunov theory,the proposed scheme allows the state errors to asymptotically converge to a specified interval.Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.展开更多
Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncerta...Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.展开更多
A robust Adaptive Discrete-time Sliding Mode Controller (ADSMC) is formulated, and is applied to control the pitch motion of a simulated Flapping-Wing Micro Air Vehicle (FWMAV). There is great potential for FWMAVs to ...A robust Adaptive Discrete-time Sliding Mode Controller (ADSMC) is formulated, and is applied to control the pitch motion of a simulated Flapping-Wing Micro Air Vehicle (FWMAV). There is great potential for FWMAVs to be used as aerial tools to assist with gathering data and surveying environments. Thanks to modern manufacturing and technology, along with an increased comprehension behind the aerodynamics of wing flaps, these vehicles are now a reality, though not without limitations. Given their diminutive size, FWMAVs are susceptible to real-world disturbances, such as wind gusts, and are sensitive to particular variations in their build quality. While external forces such as wind gusts can be reasonably bounded, the unknown variations in the state may be difficult to characterize or bound without affecting performance. To address these problems, an ADSMC is developed. First, the FWMAV model is converted from continuous-time to discrete-time. Second, an ADSMC for the newly discretized FWMAV model is developed. Using this controller, the trajectory tracking performance of the FWMAV is assessed against a traditional discrete sliding mode controller, and is found to have a decreased chattering frequency and decreased control effort for the same task. Therefore, the ADSMC is assessed as the superior controller, despite being completely unaware of the model parameters or wind gust.展开更多
Dear Editor,This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles(UUVs)to carry out maritime search and rescue(MSR)missions.The kinetic model parameters of...Dear Editor,This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles(UUVs)to carry out maritime search and rescue(MSR)missions.The kinetic model parameters of each UUV is totally unknown.Firstly,a kinematic control law is constructed by designing a vertical line-of-sight(LOS)guidance scheme.展开更多
With the advancement of connected vehicle(CV)technology,an increasing number of CVs will appear on urban roads.Data collected by CVs can be used to optimize signal parameters at intersections,thus improving traffic ef...With the advancement of connected vehicle(CV)technology,an increasing number of CVs will appear on urban roads.Data collected by CVs can be used to optimize signal parameters at intersections,thus improving traffic efficiency.In this study,we design a real-time adaptive signal control method for an arterial road with multiple intersections with low penetration rates.By utilizing vehicle arrival information collected by CVs,our method rapidly determines optimal signal phasing and timing(SPaT).The proposed adaptive signal control method was tested with the Simulation of Urban Mobility(SUMO)software,and was found to reduce total travel delay in the network better than a fixed coordination control method.The performance of the proposed method in reducing travel delay is expected to improve as CV detection range increases.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
Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed ...Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.展开更多
基金supported in part by the National Natural Science Foundation of China(62273036,62403045)the Open Research Fund of the State Key Laboratory of Multimodal Artificial Intelligence Systems(MAIS2025020)Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)(FRF-IDRY-23-036).
文摘Considering that actual systems are often constrained by multiple factors such as state limitation,actuator saturation and actuator failure at the same time,this paper provides an effective solution for non-affine multi-player systems,which can guarantee the required performance while saving communication cost.Initially,an auxiliary system is established to accommodate state limitations,following which the controller design is partitioned into two distinct segments,addressing different types of faults.Specifically,the discontinuous and continuous aspects of the controller are achieved by sliding-mode control(SMC)and adaptive critic design(ACD),respectively.During the implementation of ACD to solve the guaranteed value function incorporating the utility function designed for the asymmetric saturation of the control input,two adaptive schemes including adaptive eventtriggered impulsive control(AETIC)and adaptive self-triggered impulsive control(ASTIC)are introduced successively.It is proved that the system maintains exponential stability rather than asymptotic stability and the state signals keep ultimately uniformly bounded(UUB).Finally,the effectiveness of the proposed control sequence is verified by simulation comparisons.
基金supported in part by the National Natural Science Foundation of China(62033008,62188101,62173343,62073339)the Natural Science Foundation of Shandong Province of China(ZR2024MF072,ZR2022ZD34)the Research Fund for the Taishan Scholar Project of Shandong Province of China.
文摘This article presents an adaptive fault-tolerant tracking control strategy for unknown affine nonlinear systems subject to actuator faults and external disturbances.To address the hyperparameter initialization challenges inherent in conventional neural network training,an improved self-organizing radial basis function neural network(SRBFNN)with an input-dependent variable structure is developed.Furthermore,a novel selforganizing RBFNN-based observer is introduced to estimate system states across all dimensions.Leveraging the reconstructed states,the proposed adaptive controller effectively compensates for all uncertainties,including estimation errors in the observer,ensuring accurate state tracking with reduced control effort.The uniform ultimate boundedness of all closed-loop signals and tracking errors is rigorously established via Lyapunov stability analysis.Finally,simulations on two different nonlinear systems comprehensively validate the effectiveness and superiority of the proposed control approach.
基金Supported by the National Natural Science Foundation of China(61074080)the Innovation Foundation for Aeronautical Science and Technology(08C52001)~~
文摘A direct self-repairing control approach is proposed for helicopter via quantum control techniques and adaptive compensator when some complex faults occur. For a linear varying-parameter helicopter control system, the model reference adaptive control law is designed and an adaptive compensator is used for improving its self-re- pairing capability. To enhance anti-interference capability of helicopter, quantum control feedforward is added be- tween fault and disturbance. Simulation results illustrate the effectiveness and feasibility of the approach.
基金financially supported by the Talent Initiation Fund of Wuxi University(550220008).
文摘With the increasing integration of renewable energy,microgrids are increasingly facing stability challenges,primarily due to the lack of inherent inertia in inverter-dominated systems,which is traditionally provided by synchronous generators.To address this critical issue,Virtual Synchronous Generator(VSG)technology has emerged as a highly promising solution by emulating the inertia and damping characteristics of conventional synchronous generators.To enhance the operational efficiency of virtual synchronous generators(VSGs),this study employs smallsignal modeling analysis,root locus methods,and synchronous generator power-angle characteristic analysis to comprehensively evaluate how virtual inertia and damping coefficients affect frequency stability and power output during transient processes.Based on these analyses,an adaptive control strategy is proposed:increasing the virtual inertia when the rotor angular velocity undergoes rapid changes,while strengthening the damping coefficient when the speed deviation exceeds a certain threshold to suppress angular velocity oscillations.To validate the effectiveness of the proposed method,a grid-connected VSG simulation platform was developed inMATLAB/Simulink.Comparative simulations demonstrate that the proposed adaptive control strategy outperforms conventional VSGmethods by significantly reducing grid frequency deviations and shortening active power response time during active power command changes and load disturbances.This approach enhances microgrid stability and dynamic performance,confirming its viability for renewable-dominant power systems.Future work should focus on experimental validation and real-world parameter optimization,while further exploring the strategy’s effectiveness in improvingVSG low-voltage ride-through(LVRT)capability and power-sharing applications in multi-parallel configurations.
基金financially supported by Sichuan Science and Technology Program(Grant No.2023NSFSC1980).
文摘This study examines the adaptive boundary control problem of flexible marine riser with internal flow coupling.The dynamic model of the flexible marine riser system with internal flow coupling is derived using the Hamiltonian principle.An analysis of internal flow’s influence on the vibration characteristics of flexible marine risers is conducted.Then,for the uncertain environmental disturbance,the adaptive fuzzy logic system is introduced to dynamically approximate the boundary disturbance,and a robust adaptive fuzzy boundary control is proposed.The uniform boundedness of the closed-loop system is proved based on Lyapunov theory.The well-posedness of the closed-loop system is proved by operator semigroup theory.The proposed control’s effectiveness is validated through comparison with existing control methods.
文摘This paper explores the issue of secure synchronization control in piecewise-homogeneous Markovian jump delay neural networks affected by denial-of-service(DoS)attacks.Initially,a novel memory-based adaptive event-triggered mechanism(MBAETM)is designed based on sequential growth rates,focusing on event-triggered conditions and thresholds.Subsequently,from the perspective of defenders,non-periodic DoS attacks are re-characterized,and a model of irregular DoS attacks with cyclic fluctuations within time series is further introduced to enhance the system's defense capabilities more effectively.Additionally,considering the unified demands of network security and communication efficiency,a resilient memory-based adaptive event-triggered mechanism(RMBAETM)is proposed.A unified Lyapunov-Krasovskii functional is then constructed,incorporating a loop functional to thoroughly consider information at trigger moments.The master-slave system achieves synchronization through the application of linear matrix inequality techniques.Finally,the proposed methods'effectiveness and superiority are confirmed through four numerical simulation examples.
基金supported by National Natural Science Foundation of China(No.52302472)。
文摘The development of the adaptive cycle engine is a crucial direction of advanced fighter power sources in the near future.However,this new technology brings more uncertainty to the design of the control system.To address the versatile thrust demand under complex dynamic characteristics of the adaptive cycle engine,this paper proposes a direct thrust estimation and control method based on the Model-Free Adaptive Control(MFAC)algorithm.First,an improved Sliding Mode Control-MFAC(SMC-MFAC)algorithm has been developed by introducing a sliding mode variable structure into the standard Full Format Dynamic Linearization-MFAC(FFDL-MFAC)and designing self-adaptive weight coefficients.Then a trivariate double-loop direct thrust control structure with a controller-based thrust estimator and an outer command compensation loop has been established.Through thrust feedback and command correction,accurate control under multi-mode and operation conditions is achieved.The main contribution of this paper is the improved algorithm that combines the tracking capability of the MFAC and the robustness of the SMC,thus enhancing the dynamic performance.Considering the requirements of the online thrust feedback,the designed MFAC-based thrust estimator significantly speeds up the calculation.Additionally,the proposed command correction module can achieve the adaptive thrust control without affecting the operation of the inner loop.Simulations and Hardware-in-Loop(HIL)experiments have been performed on an adaptive cycle engine component-level model to investigate the estimation and control effect under different modes and health conditions.The results demonstrate that both the thrust estimation precision and operation speed are significantly improved compared with Extended Kalman Filter(EKF).Furthermore,the system can accelerate the response of the controlled plant,reduce the overshoot,and realize the thrust recovery within the safety range when the engine encounters the degradation.
基金supported by the National Natural Science Foundation of China under 62173172。
文摘This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an auxiliary system is established.Based on the finite-time stability theory and inverse optimal theory,a fuzzy adaptive inverse finite-time inverse optimal control method is proposed.It is proven that the formulated control approach guarantees the stability of the controlled systems,while ensuring that errors converge to a small neighborhood of zero within finite time.Moreover,the optimized control performance can be achieved.Eventually,the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.
文摘This paper investigates the problem of cluster synchronization of master-slave complex net-works with time-varying delay via linear and adaptive feedback pinning controls.We need not non-delayed and delayed coupling matrices to be symmetric or irreducible.We have the advantages of using adaptive control method to reduce control gain and pinning control technology to reduce cost.By con-structing Lyapunov function,some sufficient synchronization criteria are established.Finally,numerical examples are employed to illustrate the effectiveness of the proposed approach.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFB3403402)National Natural Science Foundation of China Basic Research Programme for PhD Students(Grant No.524B2049)。
文摘In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of pneumatic systems can significantly impact the force control accuracy of pneumatic polishing system end-effectors.To enhance responsiveness and control precision during the flexible polishing process,this study proposes an observer-based fuzzy adaptive control(OBFAC)scheme.To ensure control accuracy under an uncertain dynamic contact model,a fuzzy state observer is designed to estimate unmeasured states,while fuzzy logic approximates the uncertain nonlinear functions in the model to improve control performance.Additionally,the integral barrier Lyapunov function is employed to ensure that all states remain within predefined constraints.The stability of the proposed control scheme is analyzed using the Lyapunov function,and a pneumatic polishing experimental platform is constructed to conduct polishing contact force control experiments under multiple scenarios.Experimental results demonstrate that the proposed OBFAC scheme achieves superior tracking control performance compared to existing control schemes.
基金supported in part by the Thai Nguyen University of Technology,Vietnam.
文摘This article presents an adaptive optimal control method for a semi-active suspension system.The model of the suspension system is built,in which the components of uncertain parameters and exogenous disturbance are described.The adaptive optimal control law consists of the sum of the optimal control component and the adaptive control component.First,the optimal control law is designed for the model of the suspension system after ignoring the components of uncertain parameters and exogenous disturbance caused by the road surface.The optimal control law expresses the desired dynamic characteristics of the suspension system.Next,the adaptive component is designed with the purpose of compensating for the effects caused by uncertain parameters and exogenous disturbance caused by the road surface;the adaptive component has adaptive parameter rules to estimate uncertain parameters and exogenous disturbance.When exogenous disturbances are eliminated,the system responds with an optimal controller designed.By separating theoretically the dynamic of a semi-active suspension system,this solution allows the design of two separate controllers easily and has reduced the computational burden and the use of too many tools,thus allowing for more convenient hardware implementation.The simulation results also show the effectiveness of damping oscillations of the proposed solution in this article.
基金Supported by Key R&D Project of Zhejiang(Grant No.2022C02052)。
文摘Tracking control of tendon-driven manipulators has become a prevalent research area.However,the existence of flexible elastic tendons generates substantial residual vibrations,resulting in difficulties for trajectory tracking control of the manipulator.This paper proposes the radial basis function neural network adaptive hierarchical sliding mode control(RBFNNA-HSMC)method,which combines the dynamic model of the elastic tendon-driven manipulator(ETDM)with radial basis neural network adaptive control and hierarchical sliding mode control technology.The aim is to achieve trajectory tracking control of ETDM even under conditions of model inaccuracy and disturbance.The Lyapunov stability theory demonstrates the stability of the proposed RBFNNA-HSM controller.In order to assess the effectiveness and adaptability of the proposed control method,simulations and experiments were performed on a two-DOF ETDM.The RBFNNA-HSM method shows superior tracking accuracy compared to traditional modelbased HSM control.The experiment shows that the maximum tracking error for ETDM double-joint trajectory tracking is below 2.593×10-3rad and 1.624×10-3rad,respectively.
基金supported by the Natural Science Basic Research Program of Shaanxi with Grant No.2025JC-YBQN-807。
文摘Sliding mode control(SMC)is a well-known robust nonlinear control method with strong robustness and fast response which has been widely used in many applications.This paper introduces the major results of SMC design methods that the authors have achieved in the last decade.Undoubtedly,our results are obtained based on many other researchers'pioneer work in the literature which will not be discussed in detail here.Notably,our development has a main focus on tackling practical issues such that a proposed or enhanced SMC approach is effectively applicable to motion control systems.Issues on sliding function and adaptive gain designs in SMC and their control features will be both discussed in this paper.Those issues comprise fast convergent speed,predefined convergent time,input saturation restriction,chattering reduction,and unknown disturbance suppression.Lastly,conclusion and a few remarks on future research directions are presented.
基金supported in part by the National Key Research and Development Program of China(2023YFB4706400)the National Natural Science Foundation of China(62273112,62073030,62203161)+6 种基金the Guangdong Basic and Applied Basic Research Foundation(2023B1515120018,2023B1515120019)the Open Project of Xiangjiang Laboratory(23XJ03012)the Natural Science Foundation of Hunan Province(2024JJ5087)the Natural Science Foundation of Jiangxi Province(20232BAB212024)the National Research Foundation of Korea funded by the Ministry of Science and ICT,South Korea(IRIS-2023-00207954)the Science and Technology Planning Project of Guangzhou,China(2023A03J0120)the Guangzhou University Research Project(RC2023037)
文摘In this study,we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults.First,an inverse hysteresis dynamics model is introduced,and then the control input is divided into an expected input and an error compensator.Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis.Subsequently,by modifying the adaptive laws and local control laws,a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system.Through the direct Lyapunov theory,the proposed scheme allows the state errors to asymptotically converge to a specified interval.Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.
基金National Natural Science Foundation of China(62373102)Jiangsu Natural Science Foundation(BK20221455)Anhui Provincial Key Research and Development Project(2022i01020013)。
文摘Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.
文摘A robust Adaptive Discrete-time Sliding Mode Controller (ADSMC) is formulated, and is applied to control the pitch motion of a simulated Flapping-Wing Micro Air Vehicle (FWMAV). There is great potential for FWMAVs to be used as aerial tools to assist with gathering data and surveying environments. Thanks to modern manufacturing and technology, along with an increased comprehension behind the aerodynamics of wing flaps, these vehicles are now a reality, though not without limitations. Given their diminutive size, FWMAVs are susceptible to real-world disturbances, such as wind gusts, and are sensitive to particular variations in their build quality. While external forces such as wind gusts can be reasonably bounded, the unknown variations in the state may be difficult to characterize or bound without affecting performance. To address these problems, an ADSMC is developed. First, the FWMAV model is converted from continuous-time to discrete-time. Second, an ADSMC for the newly discretized FWMAV model is developed. Using this controller, the trajectory tracking performance of the FWMAV is assessed against a traditional discrete sliding mode controller, and is found to have a decreased chattering frequency and decreased control effort for the same task. Therefore, the ADSMC is assessed as the superior controller, despite being completely unaware of the model parameters or wind gust.
基金supported by the National Science and Technology Major Project(2022ZD0119902)the Doctoral Scientific Research Foundation of Liaoning Province(2023-BS-077)+2 种基金the Postdoctoral Research Foundation of China(2024M751980)the Open Project of State Key Laboratory of Maritime Technology and Safety(SKLMTA-DMU2024Y3)Bolian Research Funds of Dalian Maritime University/Fundamental Research Funds for the Central Universities(3132023616).
文摘Dear Editor,This letter is concerned with a coordinated path following control method for multiple unmanned underwater vehicles(UUVs)to carry out maritime search and rescue(MSR)missions.The kinetic model parameters of each UUV is totally unknown.Firstly,a kinematic control law is constructed by designing a vertical line-of-sight(LOS)guidance scheme.
基金supported by the Program of Humanities and Social Science of the Ministry of Education of China(No.24YJA630013)the Natural Science Foundation of Ningbo of China(No.2024J125)the“Innovation Yongjiang 2035”Key R&D Programme(No.2024H032),China。
文摘With the advancement of connected vehicle(CV)technology,an increasing number of CVs will appear on urban roads.Data collected by CVs can be used to optimize signal parameters at intersections,thus improving traffic efficiency.In this study,we design a real-time adaptive signal control method for an arterial road with multiple intersections with low penetration rates.By utilizing vehicle arrival information collected by CVs,our method rapidly determines optimal signal phasing and timing(SPaT).The proposed adaptive signal control method was tested with the Simulation of Urban Mobility(SUMO)software,and was found to reduce total travel delay in the network better than a fixed coordination control method.The performance of the proposed method in reducing travel delay is expected to improve as CV detection range increases.
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 National Natural Science Foundation of China under Grant U21A20449in part by Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2。
文摘Wireless communication-enabled Cooperative Adaptive Cruise Control(CACC)is expected to improve the safety and traffic capacity of vehicle platoons.Existing CACC considers a conventional communication delay with fixed Vehicular Communication Network(VCN)topologies.However,when the network is under attack,the communication delay may be much higher,and the stability of the system may not be guaranteed.This paper proposes a novel communication Delay Aware CACC with Dynamic Network Topologies(DADNT).The main idea is that for various communication delays,in order to maximize the traffic capacity while guaranteeing stability and minimizing the following error,the CACC should dynamically adjust the VCN network topology to achieve the minimum inter-vehicle spacing.To this end,a multi-objective optimization problem is formulated,and a 3-step Divide-And-Conquer sub-optimal solution(3DAC)is proposed.Simulation results show that with 3DAC,the proposed DADNT with CACC can reduce the inter-vehicle spacing by 5%,10%,and 14%,respectively,compared with the traditional CACC with fixed one-vehicle,two-vehicle,and three-vehicle look-ahead network topologies,thereby improving the traffic efficiency.
