This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires t...This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires to integrate a compensation mechanism into the event-triggered control architecture.To this end,dynamic gain and adaptive control techniques are introduced to address the effects of neutral delays,unknown hysteresis and parameter uncertainties simultaneously.By introducing a non-negative internal dynamic variable,a dynamic event-triggered controller is designed using the hyperbolic tangent function to reduce the communication burden.By means of the Lyapunov–Krasovskii method,it is demonstrated that all signals of the closed-loop system are globally bounded and eventually converge to a tunable bounded region.Moreover,the Zeno behavior is avoided.Finally,a simulation example is presented to verify the validity of the control scheme.展开更多
The problem of decentralized adaptive fuzzy control for a class of time-delayed interconnected nonlinear systems with unknown backlash-like hystersis is discussed. On the basis of the principle of variable structure c...The problem of decentralized adaptive fuzzy control for a class of time-delayed interconnected nonlinear systems with unknown backlash-like hystersis is discussed. On the basis of the principle of variable structure control （VSC） and by using the fuzzy systems with linear adjustable parameters that are used to approximate plant unknown functions, a novel decentralized adaptive fuzzy control strategy with a supervisory controller is developed. A general method, which is modeled the backlash-like hysteresis, is proposed and removes the assumption that the boundedness of disturbance, and the slope of the backlash-like hystersis are known constants. Furthermore, the interconnection term is supposed to be pth-order polynomial in time-delayed states. In addition, the plant dynamic uncertainty and modeling errors are adaptively compensated by adjusting the parameters and gains on-line for each subsystems. By theoretical analysis, it is shown that the closed-loop fuzzy control systems are globally stable, with tracking error converging to zero. Simulation results demonstrate the effectiveness of the approach.展开更多
In this study,an adaptive asymptotic tracking control problem is considered for stochastic nonlinear systems with unknown backlash-like hysteresis.By utilizing backstepping technology and bound estimation approach,an ...In this study,an adaptive asymptotic tracking control problem is considered for stochastic nonlinear systems with unknown backlash-like hysteresis.By utilizing backstepping technology and bound estimation approach,an adaptive asymptotic tracking control scheme is designed,where fuzzy systems are applied to approximate unknown function terms,the effect of hysteresis and stochastic disturbances is compensated appropriately.The proposed scheme ensures that the tracking error can asymptotically converge to zero in probability and all signals of the closed-loop system are bounded almost surely.Finally,the effectiveness of the control scheme is verified by giving a simulation example.展开更多
In this paper,a cooperative adaptive control of leader-following uncertain nonlinear multiagent systems is proposed.The communication network is weighted undirected graph with fixed topology.The uncertain nonlinear mo...In this paper,a cooperative adaptive control of leader-following uncertain nonlinear multiagent systems is proposed.The communication network is weighted undirected graph with fixed topology.The uncertain nonlinear model for each agent is a higher-order integrator with unknown nonlinear functions,unknown disturbances and unknown input actuators.Meanwhile,the gains of input actuators are unknown nonlinear functions with unknown sign.Two most common behaviors of input actuators in practical applications are hysteresis and dead-zone.In this paper,backlash-like hysteresis and dead-zone are used to model the input actuators.Using universal approximation theorem proved for neural networks,the unknown nonlinear functions are tackled.The unknown weights of neural networks are derived by proposing appropriate adaptive laws.To cope with modeling errors and disturbances an adaptive robust structure is proposed.Considering Lyapunov synthesis approach not only all the adaptive laws are derived but also it is proved that the closed-loop network is cooperatively semi-globally uniformly ultimately bounded(CSUUB).In order to investigate the effectiveness of the proposed method,it is applied to agents modeled with highly nonlinear mathematical equations and inverted pendulums.Simulation results demonstrate the effectiveness and applicability of the proposed method in dealing with both numerical and practical multi-agent systems.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62073190the Science Center Program of National Natural Science Foundation of China under Grant 62188101.
文摘This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires to integrate a compensation mechanism into the event-triggered control architecture.To this end,dynamic gain and adaptive control techniques are introduced to address the effects of neutral delays,unknown hysteresis and parameter uncertainties simultaneously.By introducing a non-negative internal dynamic variable,a dynamic event-triggered controller is designed using the hyperbolic tangent function to reduce the communication burden.By means of the Lyapunov–Krasovskii method,it is demonstrated that all signals of the closed-loop system are globally bounded and eventually converge to a tunable bounded region.Moreover,the Zeno behavior is avoided.Finally,a simulation example is presented to verify the validity of the control scheme.
基金partially supported by the National Natural Science Foundation of China (60874045,60774017).
文摘The problem of decentralized adaptive fuzzy control for a class of time-delayed interconnected nonlinear systems with unknown backlash-like hystersis is discussed. On the basis of the principle of variable structure control （VSC） and by using the fuzzy systems with linear adjustable parameters that are used to approximate plant unknown functions, a novel decentralized adaptive fuzzy control strategy with a supervisory controller is developed. A general method, which is modeled the backlash-like hysteresis, is proposed and removes the assumption that the boundedness of disturbance, and the slope of the backlash-like hystersis are known constants. Furthermore, the interconnection term is supposed to be pth-order polynomial in time-delayed states. In addition, the plant dynamic uncertainty and modeling errors are adaptively compensated by adjusting the parameters and gains on-line for each subsystems. By theoretical analysis, it is shown that the closed-loop fuzzy control systems are globally stable, with tracking error converging to zero. Simulation results demonstrate the effectiveness of the approach.
基金supported in part by the Natural Science Foundation of Shandong Province for Key Projects under Grant No.ZR2020KA010in part by the National Natural Science Foundation of China under Grant No.62073187+1 种基金in part by the Major Scientific and Technological Innovation Project in Shandong Province under Grant No.2019JZZY011111“Guangyue Young Scholar Innovation Team”of Liaocheng University under Grant No.LCUGYTD2022-01。
文摘In this study,an adaptive asymptotic tracking control problem is considered for stochastic nonlinear systems with unknown backlash-like hysteresis.By utilizing backstepping technology and bound estimation approach,an adaptive asymptotic tracking control scheme is designed,where fuzzy systems are applied to approximate unknown function terms,the effect of hysteresis and stochastic disturbances is compensated appropriately.The proposed scheme ensures that the tracking error can asymptotically converge to zero in probability and all signals of the closed-loop system are bounded almost surely.Finally,the effectiveness of the control scheme is verified by giving a simulation example.
基金Supported by National Natural Science Foundation of China（60874044） Research Foundation for Key Disciplines of Beijing Municipal Commission of Education （XK100060422）
文摘In this paper,a cooperative adaptive control of leader-following uncertain nonlinear multiagent systems is proposed.The communication network is weighted undirected graph with fixed topology.The uncertain nonlinear model for each agent is a higher-order integrator with unknown nonlinear functions,unknown disturbances and unknown input actuators.Meanwhile,the gains of input actuators are unknown nonlinear functions with unknown sign.Two most common behaviors of input actuators in practical applications are hysteresis and dead-zone.In this paper,backlash-like hysteresis and dead-zone are used to model the input actuators.Using universal approximation theorem proved for neural networks,the unknown nonlinear functions are tackled.The unknown weights of neural networks are derived by proposing appropriate adaptive laws.To cope with modeling errors and disturbances an adaptive robust structure is proposed.Considering Lyapunov synthesis approach not only all the adaptive laws are derived but also it is proved that the closed-loop network is cooperatively semi-globally uniformly ultimately bounded(CSUUB).In order to investigate the effectiveness of the proposed method,it is applied to agents modeled with highly nonlinear mathematical equations and inverted pendulums.Simulation results demonstrate the effectiveness and applicability of the proposed method in dealing with both numerical and practical multi-agent systems.
