Chenliang Wang

Decentralized adaptive tracking control for a class of interconnected nonlinear time-varying systems

In this paper, aiming at output tracking, a decentralized adaptive backstepping control scheme is proposed for a class of interconnected nonlinear time-varying systems. By introducing a bound estimation approach and two smooth functions, the obstacle caused by unknown time-varying parameters and unknown interactions is circumvented and all signals of the overall closed-loop system are proved to be globally uniformly bounded, without any restriction on the parameters variation speed. Moreover, it is shown that the tracking errors can converge to predefined arbitrarily small residual sets with prescribed convergence rate and maximum overshoot, independent of the parameters variation speed and the strength of interactions. Simulation results performed on double inverted pendulums are presented to illustrate the effectiveness of the proposed scheme.

Decentralized adaptive backstepping control for a class of interconnected nonlinear systems with unknown actuator failures

Abstract In this paper, a decentralized adaptive backstepping control scheme is proposed for a class of interconnected nonlinear systems with unknown actuator failures. By introducing a smooth function, some integrable auxiliary signals and a bound estimation approach, the effect of actuator failures is successfully compensated for. The proposed scheme has the following features: (1) the total number of failures is allowed to be infinite; (2) global stability of the overall closed-loop system is achieved without any bound knowledge of uncertainties; (3) all system outputs converge to zero asymptotically regardless of the possibly infinite number of failures and the unknown interactions among subsystems. Simulation results on coupled inverted double pendulums are presented to illustrate the effectiveness of the proposed scheme.

Decentralized output-feedback adaptive control for a class of interconnected nonlinear systems with unknown actuator failures

In this paper, a decentralized output-feedback adaptive backstepping control scheme is proposed for a class of interconnected nonlinear systems with unknown actuator failures. By introducing a kind of high-gain K -filters, a bound estimation approach and some smooth functions, the effect of actuator failures and interactions among subsystems is successfully compensated for and the actuators are allowed to change among the normal operation case and different failure cases infinitely many times. The proposed scheme is able to guarantee the global stability of the overall closed-loop system, regardless of the possibly infinite number of unknown actuator failures. An initialization technique is also introduced so that the L ∞ performance of tracking errors can be adjusted no matter if there exist unknown actuator failures. Simulation results performed on double inverted pendulums are presented to illustrate the effectiveness of the proposed scheme.

Adaptive Actuator Failure Compensation for a Class of Nonlinear Systems With Unknown Control Direction

In this note, a novel adaptive compensation control scheme is proposed for a class of nonlinear systems with unknown control direction and a possibly infinite number of unknown actuator failures. By introducing a bound estimation approach, high-order Lyapunov functions and a Nussbaum function with faster growth rate, the obstacle caused by unknown failures and unknown control direction is successfully circumvented and all signals of the closed-loop system are proved to be globally uniformly bounded. Moreover, the proposed scheme is able to steer the tracking error into a predefined small residue set. Simulation results are presented to illustrate the effectiveness of the proposed scheme.

Decentralized adaptive tracking control for a class of interconnected nonlinear systems with input quantization

Abstract In this paper, a decentralized output-feedback adaptive control scheme is proposed for a class of interconnected nonlinear systems with input quantization. Both logarithmic quantizers and improved hysteretic quantizers are studied, and a linear time-varying model is introduced to handle the difficulty caused by quantization. The proposed scheme allows the parameters of the quantizers to be freely changed during operation, and can guarantee global stability of the overall closed-loop system regardless of the coarseness of the quantizers and the existence of interactions among subsystems. Moreover, with the aid of a kind of high-gain K-filters, it is shown that all tracking errors converge to a residual set which can be made arbitrarily small by adjusting some design parameters. Simulation results are presented to illustrate the effectiveness of the proposed scheme.

Distributed Adaptive Containment Control for a Class of Nonlinear Multiagent Systems With Input Quantization

This paper is devoted to distributed adaptive containment control for a class of nonlinear multiagent systems with input quantization. By employing a matrix factorization and a novel matrix normalization technique, some assumptions involving control gain matrices in existing results are relaxed. By fusing the techniques of sliding mode control and backstepping control, a two-step design method is proposed to construct controllers and, with the aid of neural networks, all system nonlinearities are allowed to be unknown. Moreover, a linear time-varying model and a similarity transformation are introduced to circumvent the obstacle brought by quantization, and the controllers need no information about the quantizer parameters. The proposed scheme is able to ensure the boundedness of all closed-loop signals and steer the containment errors into an arbitrarily small residual set. The simulation results illustrate the effectiveness of the scheme.

Adaptive cooperative tracking control for a class of nonlinear time-varying multi-agent systems

Abstract In this paper, an adaptive cooperative tracking control scheme is proposed for a class of high-order nonlinear time-varying multi-agent systems, where only the output of the leader is available for some followers. By introducing a bound estimation approach and a smooth function, the obstacle caused by unknown time-varying parameters is successfully circumvented without any restriction on their variation speed. With the aid of the dynamic surface control technique, simple distributed adaptive controllers are obtained and each follower needs only the first two states rather than the full states of its neighbor followers, which considerably reduces the computational and communication burden. It is shown that all tracking errors converge to a residual set which can be made arbitrarily small. Simulation results on robotic manipulators are presented to illustrate the effectiveness of the proposed scheme.