Dear Editor,This letter deals with the autonomous underwater vehicle(AUV)three dimensional(3D)trajectory tracking control chronically suffering from poor accuracy and efficiency in complex hydrodynamics.A state-of-the...Dear Editor,This letter deals with the autonomous underwater vehicle(AUV)three dimensional(3D)trajectory tracking control chronically suffering from poor accuracy and efficiency in complex hydrodynamics.A state-of-the-art predictive adaptive controller(PAC)is proposed with a distinct dual closed-loop structure.展开更多
This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Consi...This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Considering the complex working environment and the stability differences in communication links between leaders and followers,a double semi-Markov process is first introduced to describe the random switching of communication topologies in the leader-follower structure.In order to address challenges from the unknown nonidentical control directions and partial loss of effectiveness actuator faults,a completely independent parameter is introduced into the Nussbaum function to overcome the inherent obstacle of mutual cancellation and avoid the rapid growth rate.Considering only the state information of agents is transmitted among the agents,an adaptive distributed fault-tolerant consensus tracking control is proposed based on the double semi-Markovian switching topologies using the designed Nussbaum function.Furthermore,the stability of the closed-loop nonlinear multi-agent systems is analyzed using contradiction argument and Lyapunov theorem,from which the asymptotic consensus tracking in mean square sense can be obtained.A numerical simulation example is provided to verify the effectiveness of the proposed algorithm.展开更多
Unmanned aircraft are highly vulnerable to crosswind-induced turbulence during complex maneuvers such as turning,which can significantly compromise control and reduce autopilot effectiveness.This paper presents a nove...Unmanned aircraft are highly vulnerable to crosswind-induced turbulence during complex maneuvers such as turning,which can significantly compromise control and reduce autopilot effectiveness.This paper presents a novel control strategy to improve the controllability of unmanned aircraft in challenging wind conditions.First,the equations of motion for the aircraft are reformulated as a system of stochastic differential equations,which are subsequently transformed into a deterministic form.By modeling turbulence as a Gaussian random process and incorporating it directly into the control system,the proposed method proactively compensates for the adverse effects of turbulence.The transformation is achieved using semi-invariant techniques.Second,the control problem is formulated as an optimization task,aiming to minimize the deviation between the actual and desired turn characteristics,specifically the angular velocity.Finally,a new numerical method with proven global convergence is employed to compute the optimal autopilot parameters.Simulation results using a medium-range unmanned aircraft model under continuous turbulent gusts demonstrate that the proposed method significantly outperforms existing approaches,ensuring both stability and precision in turbulent wind conditions.展开更多
In this paper,a practical method named linear active disturbance rejection control(LADRC)with adaptive tuning is proposed for attitude control of small-scale unmanned helicopter.The proposed method accounts for both e...In this paper,a practical method named linear active disturbance rejection control(LADRC)with adaptive tuning is proposed for attitude control of small-scale unmanned helicopter.The proposed method accounts for both external disturbances and internal dynamic uncertainties,as well as parameter deviations arising from parameter uncertainty,while maintaining a relatively small number of adjustable parameters.Furthermore,it addresses the limitation that conventional active disturbance rejection control methods cannot be rigorously analyzed for stability.The total disturbance of unmanned helicopter is estimated and compensated by designed LADRC.The introduction of adaptive control realizes online parameter tuning,which eliminates parameter deviation and further improves control precision.Moreover,it also provides a novel idea to prove the stability of controller,so that it can be analyzed by Lyapunov function.Finally,the anti-disturbance performance and effectiveness of proposed method are verified by numerical simulation.展开更多
This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temp...This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.展开更多
This paper investigates the platoon control of heterogeneous vehicular cyber-physical systems(VCPSs) subject to external disturbances by using neural network and uniformly quantized communication data.To reduce the ad...This paper investigates the platoon control of heterogeneous vehicular cyber-physical systems(VCPSs) subject to external disturbances by using neural network and uniformly quantized communication data.To reduce the adverse effects of quantization errors on system performance,a coupling sliding mode surface is established for each following vehicle.The radial basis function(RBF) neural networks are employed to approximate the unknown external disturbances.Then,a novel platoon control law is proposed for cooperative tracking in which each following vehicle only uses the uniformly quantized data of the neighboring vehicles.And the designed controllers in this paper are fully distributed due to the fact that the selection of each vehicle's controller parameters is independent of the entire communication topology.The string stability of VCPSs in the entire control process is ensured rather than only ensuring the string stability after the sliding mode surface converges to zero.Compared with the existing controller design methods and quantization mechanisms,the neural adaptive sliding-mode platoon controller proposed in this paper is superior in performances including tracking errors,driving comfort and fuel economy.Numerical simulations illustrate the effectiveness and superiority of the designed control strategy.展开更多
Realizing optimal control performance for continuum robots(CRs) poses huge challenges on traditional modelbased optimal control approaches due to their high degrees of freedom,complex nonlinear dynamics and soft conti...Realizing optimal control performance for continuum robots(CRs) poses huge challenges on traditional modelbased optimal control approaches due to their high degrees of freedom,complex nonlinear dynamics and soft continuum morphologies which are difficult to explicitly model.This paper proposes a model-free adaptive optimal control algorithm(ADAPT)for CRs.In our strategy,we consider CRs as a class of nonlinear continuous-time dynamical systems in the state space,wherein the position of the end-effector is considered as the state and the input torque is mapped as the control input.Then,the optimized Hamilton-Jacobi-Bellman(HJB) equation is derived by optimal control principles,and subsequently solved by the proposed ADAPT algorithm without requiring knowledge of the original system dynamics.Under some mild assumptions,the global stability and convergence of the closed-loop control approach are guaranteed.Several simulation experiments are conducted on a magnetic CR(MCR) to demonstrate the practicality and effectiveness of the ADAPT algorithm.展开更多
In this paper,a security defense issue is investigated for networked control systems susceptible to stochastic denial of service(DoS) attacks by using the sliding mode control method.To utilize network communication r...In this paper,a security defense issue is investigated for networked control systems susceptible to stochastic denial of service(DoS) attacks by using the sliding mode control method.To utilize network communication resources more effectively,a novel adaptive event-triggered(AET) mechanism is introduced,whose triggering coefficient can be adaptively adjusted according to the evolution trend of system states.Differing from existing event-triggered(ET) mechanisms,the proposed one demonstrates exceptional relevance and flexibility.It is closely related to attack probability,and its triggering coefficient dynamically adjusts depending on the presence or absence of an attack.To leverage attacker information more effectively,a switching-like sliding mode security controller is designed,which can autonomously select different controller gains based on the sliding function representing the attack situation.Sufficient conditions for the existence of the switching-like sliding mode secure controller are presented to ensure the stochastic stability of the system and the reachability of the sliding surface.Compared with existing time-invariant control strategies within the triggered interval,more resilient defense performance can be expected since the correlation with attack information is established in both the proposed AET scheme and the control strategy.Finally,a simulation example is conducted to verify the effectiveness and feasibility of the proposed security control method.展开更多
The increasing demand for artillery firepower,coupled with the growing size of gun barrels,imposes significant challenges on servo system performance.To address these challenges while ensuring fast and stable response...The increasing demand for artillery firepower,coupled with the growing size of gun barrels,imposes significant challenges on servo system performance.To address these challenges while ensuring fast and stable response,this paper proposes an adaptive robust controller based on an asymmetric barrier Lyapunov function(ABLF).The controller design incorporates both load and driver states through a backstepping synthesis.The overshoot and lag of barrel position errors are constrained within asymmetric boundaries,accounting for complex rotational uncertainties via an adaptive law and linear extended state observers(LESO).Simulations and experiments under typical artillery operating conditions validate the effectiveness and dynamic tracking performance of the proposed control strategy in comparison with other methods.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
Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo...Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo system. The controller design requires no information about the structure of linear servo system, and it is based on the estimation and forecasting of the pseudo-partial derivatives(PPD) which are estimated according to the voltage input and position output of the linear motor. The characteristics and operational mechanism of the permanent magnet synchronous linear motor(PMSLM) are introduced, and the proposed nonparametric model control strategy has been compared with the classic proportional-integral-derivative(PID) control algorithm. Several real-time experiments on the motion control system incorporating a permanent magnet synchronous linear motor showed that the nonparametric model adaptive control method improved the system s response to disturbances and its position-tracking precision, even for a nonlinear system with incompletely known dynamic characteristics.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
The stability of supersonic inlets faces challenges due to various changes in flight conditions,and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet...The stability of supersonic inlets faces challenges due to various changes in flight conditions,and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet developmental requirements.This paper proposes an adaptive bump control scheme and employs dynamic mesh technology for numerical simulation to investigate the unsteady control effects of adaptive bumps.The obtained results indicate that the use of moving bumps to control shock wave/boundary layer interactions is feasible.The adaptive control effects of five different bump speeds are evaluated.Within the range of bump speeds studied,the analysis of the flow field structure reveals the patterns of change in the separation zone area during the control process,as well as the relationship between the bump motion speed and the control effect on the separation zone.It is concluded that the moving bump endows the boundary layer with additional energy.展开更多
In recent times,multiple Unmanned Aerial Vehicles(UAVs)are being widely utilized in several areas of applications such as agriculture,surveillance,disaster management,search and rescue operations.Degree of robustness ...In recent times,multiple Unmanned Aerial Vehicles(UAVs)are being widely utilized in several areas of applications such as agriculture,surveillance,disaster management,search and rescue operations.Degree of robustness of applied control schemes determines how accurate a swarm of UAVs accomplish group tasks.Formation and trajectory tracking controllers are required for the swarm of multiple UAVs.Factors like external environmental effects,parametric uncertainties and wind gusts make the controller design process as a challenging task.This article proposes fractional order formation and trajectory tacking controllers for multiple quad-rotors using Super Twisting Sliding Mode Control(STSMC)technique.To compensate the effects of the disturbances due to parametric uncertainties and wind gusts,Lyapunov function based adaptive controllers are formulated.Moreover,Lyapunov theorem is used to guarantee the stability of the proposed controllers.Three types of controllers,namely fixed gain STSMC and fractional order Adaptive Super Twisting Sliding Mode Control(ASTSMC)methods are tested for the swarm of UAVs by performing the numerical simulations in MATLAB/Simulink environment.From the presented results,it is verified that in presence of wind disturbances and parametric uncertainties,the proposed fractional order ASTSMC technique showed improved robustness as compared to the fixed gain STSMC and integer order ASTSMC.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
Dear Editor,It is well known that event-triggered control(ETC)is an effective approach in addressing networked control problems for Industry 5.0.Its feasibility,however,is still restricted to canonical nonlinear syste...Dear Editor,It is well known that event-triggered control(ETC)is an effective approach in addressing networked control problems for Industry 5.0.Its feasibility,however,is still restricted to canonical nonlinear systems so far.Considering this,a gradient-based adaptive ETC scheme for noncanonical nonlinear systems is newly developed in this letter,where the hysteresis input constraints are considered also.By proper decomposition,the technical issue of handling ETC-induced measurement errors and hysteresis inputs can be transformed into the robustness problem to bounded disturbance-like terms,which is then addressed by integrating a switching modification strategy in adaptive design and developing a novel augmented error-based analysis framework.Experimental results based on a practical piezoactuator confirm the effectiveness of the proposed scheme.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
基金supported by the National Natural Science Foundation of China(U24B20183)the Pioneer Leading Goose+X Science and Technology Program of Zhejiang Province(2025C02018)。
文摘Dear Editor,This letter deals with the autonomous underwater vehicle(AUV)three dimensional(3D)trajectory tracking control chronically suffering from poor accuracy and efficiency in complex hydrodynamics.A state-of-the-art predictive adaptive controller(PAC)is proposed with a distinct dual closed-loop structure.
基金supported by the National Natural Science Foundation of China(62333011,62020106003)the Natural Science Foundation of Jiangsu Province of China(BK20222012)+1 种基金the Fundamental Research Funds for the Central Universities(NE2024005)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0594)。
文摘This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Considering the complex working environment and the stability differences in communication links between leaders and followers,a double semi-Markov process is first introduced to describe the random switching of communication topologies in the leader-follower structure.In order to address challenges from the unknown nonidentical control directions and partial loss of effectiveness actuator faults,a completely independent parameter is introduced into the Nussbaum function to overcome the inherent obstacle of mutual cancellation and avoid the rapid growth rate.Considering only the state information of agents is transmitted among the agents,an adaptive distributed fault-tolerant consensus tracking control is proposed based on the double semi-Markovian switching topologies using the designed Nussbaum function.Furthermore,the stability of the closed-loop nonlinear multi-agent systems is analyzed using contradiction argument and Lyapunov theorem,from which the asymptotic consensus tracking in mean square sense can be obtained.A numerical simulation example is provided to verify the effectiveness of the proposed algorithm.
基金co-supported by the Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan Province(No.22kftk01)the Key Research and Development Program of Heilongjiang,China(No.2024ZXJ07B05)the National Natural Science Foundation of China(No.92471103)。
文摘Unmanned aircraft are highly vulnerable to crosswind-induced turbulence during complex maneuvers such as turning,which can significantly compromise control and reduce autopilot effectiveness.This paper presents a novel control strategy to improve the controllability of unmanned aircraft in challenging wind conditions.First,the equations of motion for the aircraft are reformulated as a system of stochastic differential equations,which are subsequently transformed into a deterministic form.By modeling turbulence as a Gaussian random process and incorporating it directly into the control system,the proposed method proactively compensates for the adverse effects of turbulence.The transformation is achieved using semi-invariant techniques.Second,the control problem is formulated as an optimization task,aiming to minimize the deviation between the actual and desired turn characteristics,specifically the angular velocity.Finally,a new numerical method with proven global convergence is employed to compute the optimal autopilot parameters.Simulation results using a medium-range unmanned aircraft model under continuous turbulent gusts demonstrate that the proposed method significantly outperforms existing approaches,ensuring both stability and precision in turbulent wind conditions.
基金supported by the Aeronautical Science Foundation of China(Nos.20220058052002,20240007052001)。
文摘In this paper,a practical method named linear active disturbance rejection control(LADRC)with adaptive tuning is proposed for attitude control of small-scale unmanned helicopter.The proposed method accounts for both external disturbances and internal dynamic uncertainties,as well as parameter deviations arising from parameter uncertainty,while maintaining a relatively small number of adjustable parameters.Furthermore,it addresses the limitation that conventional active disturbance rejection control methods cannot be rigorously analyzed for stability.The total disturbance of unmanned helicopter is estimated and compensated by designed LADRC.The introduction of adaptive control realizes online parameter tuning,which eliminates parameter deviation and further improves control precision.Moreover,it also provides a novel idea to prove the stability of controller,so that it can be analyzed by Lyapunov function.Finally,the anti-disturbance performance and effectiveness of proposed method are verified by numerical simulation.
文摘This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.
基金supported by the National Natural Science Foundation of China(62173079,62473203)Liaoning Provincial Science and Technology Plan Joint Program(2024-MSLH-019)+1 种基金the Education Department of Liaoning Province(LJKMZ20221840)Interdisciplinary project of Dalian University(DLUXK-2024-YB-004)。
文摘This paper investigates the platoon control of heterogeneous vehicular cyber-physical systems(VCPSs) subject to external disturbances by using neural network and uniformly quantized communication data.To reduce the adverse effects of quantization errors on system performance,a coupling sliding mode surface is established for each following vehicle.The radial basis function(RBF) neural networks are employed to approximate the unknown external disturbances.Then,a novel platoon control law is proposed for cooperative tracking in which each following vehicle only uses the uniformly quantized data of the neighboring vehicles.And the designed controllers in this paper are fully distributed due to the fact that the selection of each vehicle's controller parameters is independent of the entire communication topology.The string stability of VCPSs in the entire control process is ensured rather than only ensuring the string stability after the sliding mode surface converges to zero.Compared with the existing controller design methods and quantization mechanisms,the neural adaptive sliding-mode platoon controller proposed in this paper is superior in performances including tracking errors,driving comfort and fuel economy.Numerical simulations illustrate the effectiveness and superiority of the designed control strategy.
基金supported in part by the Innovation and Technology Commission of Hong Kong,China(ITS/136/20,ITS/234/21,MHP/096/22,ITS/235/22)Multi-Scale Medical Robotics Center,InnoHK,China(8312051)+1 种基金Research Grants Council(RGC) of Hong Kong,China(CUHK 14217822,CUHK14207823,AoE/E-407/24-N)The Chinese University of Hong Kong(CUHK) Direct Grant。
文摘Realizing optimal control performance for continuum robots(CRs) poses huge challenges on traditional modelbased optimal control approaches due to their high degrees of freedom,complex nonlinear dynamics and soft continuum morphologies which are difficult to explicitly model.This paper proposes a model-free adaptive optimal control algorithm(ADAPT)for CRs.In our strategy,we consider CRs as a class of nonlinear continuous-time dynamical systems in the state space,wherein the position of the end-effector is considered as the state and the input torque is mapped as the control input.Then,the optimized Hamilton-Jacobi-Bellman(HJB) equation is derived by optimal control principles,and subsequently solved by the proposed ADAPT algorithm without requiring knowledge of the original system dynamics.Under some mild assumptions,the global stability and convergence of the closed-loop control approach are guaranteed.Several simulation experiments are conducted on a magnetic CR(MCR) to demonstrate the practicality and effectiveness of the ADAPT algorithm.
基金supported in part by Shanghai Natural Science Foundation(24ZR1454700)the National Natural Science Foundation of China(62503331,62533016,62573279,62173231,62203288)Shanghai Pujiang Program(23PJD033)。
文摘In this paper,a security defense issue is investigated for networked control systems susceptible to stochastic denial of service(DoS) attacks by using the sliding mode control method.To utilize network communication resources more effectively,a novel adaptive event-triggered(AET) mechanism is introduced,whose triggering coefficient can be adaptively adjusted according to the evolution trend of system states.Differing from existing event-triggered(ET) mechanisms,the proposed one demonstrates exceptional relevance and flexibility.It is closely related to attack probability,and its triggering coefficient dynamically adjusts depending on the presence or absence of an attack.To leverage attacker information more effectively,a switching-like sliding mode security controller is designed,which can autonomously select different controller gains based on the sliding function representing the attack situation.Sufficient conditions for the existence of the switching-like sliding mode secure controller are presented to ensure the stochastic stability of the system and the reachability of the sliding surface.Compared with existing time-invariant control strategies within the triggered interval,more resilient defense performance can be expected since the correlation with attack information is established in both the proposed AET scheme and the control strategy.Finally,a simulation example is conducted to verify the effectiveness and feasibility of the proposed security control method.
文摘The increasing demand for artillery firepower,coupled with the growing size of gun barrels,imposes significant challenges on servo system performance.To address these challenges while ensuring fast and stable response,this paper proposes an adaptive robust controller based on an asymmetric barrier Lyapunov function(ABLF).The controller design incorporates both load and driver states through a backstepping synthesis.The overshoot and lag of barrel position errors are constrained within asymmetric boundaries,accounting for complex rotational uncertainties via an adaptive law and linear extended state observers(LESO).Simulations and experiments under typical artillery operating conditions validate the effectiveness and dynamic tracking performance of the proposed control strategy in comparison with other methods.
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.
基金supported by Beijing Natural Science Foundation(No.4142017)International Cooperation Project of National Natural Science Foundation of China(No.61120106009)Beijing Science and Technology Commission Precision Machinery Projects(No.Z121100001612007)
文摘Nowadays, high-precision motion controls are needed in modern manufacturing industry. A data-driven nonparametric model adaptive control(NMAC) method is proposed in this paper to control the position of a linear servo system. The controller design requires no information about the structure of linear servo system, and it is based on the estimation and forecasting of the pseudo-partial derivatives(PPD) which are estimated according to the voltage input and position output of the linear motor. The characteristics and operational mechanism of the permanent magnet synchronous linear motor(PMSLM) are introduced, and the proposed nonparametric model control strategy has been compared with the classic proportional-integral-derivative(PID) control algorithm. Several real-time experiments on the motion control system incorporating a permanent magnet synchronous linear motor showed that the nonparametric model adaptive control method improved the system s response to disturbances and its position-tracking precision, even for a nonlinear system with incompletely known dynamic characteristics.
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.
基金supported by the National Key R&D Program of China(Grant No.2019YFA0405300)the National Natural Science Foundation of China(Grant No.11972368)the Natural Science Foundation of Hunan Province(Grant No.2021JJ10045).
文摘The stability of supersonic inlets faces challenges due to various changes in flight conditions,and flow control methods that address shock wave/boundary layer interactions under only one set of conditions cannot meet developmental requirements.This paper proposes an adaptive bump control scheme and employs dynamic mesh technology for numerical simulation to investigate the unsteady control effects of adaptive bumps.The obtained results indicate that the use of moving bumps to control shock wave/boundary layer interactions is feasible.The adaptive control effects of five different bump speeds are evaluated.Within the range of bump speeds studied,the analysis of the flow field structure reveals the patterns of change in the separation zone area during the control process,as well as the relationship between the bump motion speed and the control effect on the separation zone.It is concluded that the moving bump endows the boundary layer with additional energy.
基金supported by Prince of Songkla Universitythe Ministry of Higher Education,Science,Research and Innovation,under the Reinventing University Project(No.REV64022)。
文摘In recent times,multiple Unmanned Aerial Vehicles(UAVs)are being widely utilized in several areas of applications such as agriculture,surveillance,disaster management,search and rescue operations.Degree of robustness of applied control schemes determines how accurate a swarm of UAVs accomplish group tasks.Formation and trajectory tracking controllers are required for the swarm of multiple UAVs.Factors like external environmental effects,parametric uncertainties and wind gusts make the controller design process as a challenging task.This article proposes fractional order formation and trajectory tacking controllers for multiple quad-rotors using Super Twisting Sliding Mode Control(STSMC)technique.To compensate the effects of the disturbances due to parametric uncertainties and wind gusts,Lyapunov function based adaptive controllers are formulated.Moreover,Lyapunov theorem is used to guarantee the stability of the proposed controllers.Three types of controllers,namely fixed gain STSMC and fractional order Adaptive Super Twisting Sliding Mode Control(ASTSMC)methods are tested for the swarm of UAVs by performing the numerical simulations in MATLAB/Simulink environment.From the presented results,it is verified that in presence of wind disturbances and parametric uncertainties,the proposed fractional order ASTSMC technique showed improved robustness as compared to the fixed gain STSMC and integer order ASTSMC.
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.
文摘Dear Editor,It is well known that event-triggered control(ETC)is an effective approach in addressing networked control problems for Industry 5.0.Its feasibility,however,is still restricted to canonical nonlinear systems so far.Considering this,a gradient-based adaptive ETC scheme for noncanonical nonlinear systems is newly developed in this letter,where the hysteresis input constraints are considered also.By proper decomposition,the technical issue of handling ETC-induced measurement errors and hysteresis inputs can be transformed into the robustness problem to bounded disturbance-like terms,which is then addressed by integrating a switching modification strategy in adaptive design and developing a novel augmented error-based analysis framework.Experimental results based on a practical piezoactuator confirm the effectiveness of the proposed scheme.
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.
