Lantao Xing

Output feedback control for uncertain nonlinear systems with input quantization

In this paper, we propose a new adaptive output-feedback tracking control scheme for a class of uncertain nonlinear systems with input quantized by a newly-proposed quantizer. This quantizer is a combination of a logarithmic (or a hysteresis) quantizer and a uniform quantizer, and it has the advantages of both logarithmic and uniform quantizers in ensuring reducible communication expenses and acceptable quantization errors for better system performances. Compared with existing results in adaptive control, the proposed scheme provides a way to relax certain restrictive conditions, in addition to solving the problem of adaptive output-feedback control with input quantization. It is shown that the designed adaptive controller ensures global boundedness of all the signals in the closed-loop system and enables the tracking error to exponentially converge towards a compact set which is adjustable.

Event-Triggered Adaptive Control for a Class of Uncertain Nonlinear Systems

In this technical note, the problem of event-trigger based adaptive control for a class of uncertain nonlinear systems is considered. The nonlinearities of the system are not required to be globally Lipschitz. Since the system contains unknown parameters, it is a difficult task to check the assumption of the input-to-state stability (ISS) with respect to the measurement errors, which is required in most existing literature. To solve this problem, we design both the adaptive controller and the triggering event at the same time such that the ISS assumption is no longer needed. In addition to presenting new design methodologies based on the fixed threshold strategy and relative threshold strategy, we also propose a new strategy named the switching threshold strategy. It is shown that the proposed control schemes guarantee that all the closed-loop signals are globally bounded and the tracking/stabilization error exponentially converges towards a compact set which is adjustable.

A new adaptive control scheme for uncertain nonlinear systems with quantized input signal

Abstract In this paper,we propose a new simple yet effective adaptive tracking control scheme for uncertain strict-feedback nonlinear systems whose input is quantized by a class of sector-bounded quantizers including the well-known logarithmic quantizer and the extended hysteresis quantizer . To deal with the error caused by quantization, a key technique is to utilize the sector bound property of the quantizers directly instead of decomposing it into a linear part and a nonlinear part. Compared with the existing results in adaptive control, the proposed scheme relaxes the global Lipschitz conditions of nonlinearities and the boundedness of their partial derivatives. It is shown that the designed adaptive controller ensures global boundedness of all the signals in the closed-loop system and enables the tracking error to exponentially converge towards a compact set which is adjustable.

Event-Based Consensus for Linear Multiagent Systems Without Continuous Communication

In this paper, we propose a new distributed event-trigger consensus protocol for linear multiagent systems with external disturbances. Two consensus problems are considered: one is a leader-follower case and the other is a nonleader case. Different from the existing results, our proposed scheme enables each agent to decide when to transmit its state signals to its neighbors such that continuous communication between neighboring agents is avoided. Clearly, this can largely decrease the communication burden of the whole communication network. Besides, since the control signal for each agent is discontinuous because of the event-triggering mechanism, the existence of a solution for the closed-loop system in the classical sense may not be guaranteed. To solve this problem, we employ a nonsmooth analysis technique including differential inclusion and Filippov solution. Through nonsmooth Lyapunov analysis, it is shown that uniformly bounded consensus results are derived and the bound of the consensus error is adjustable by choosing suitable design parameters.In this paper, we propose a new distributed event-trigger consensus protocol for linear multiagent systems with external disturbances. Two consensus problems are considered: one is a leader–follower case and the other is a nonleader case. Different from the existing results, our proposed scheme enables each agent to decide when to transmit its state signals to its neighbors such that continuous communication between neighboring agents is avoided. Clearly, this can largely decrease the communication burden of the whole communication network. Besides, since the control signal for each agent is discontinuous because of the event-triggering mechanism, the existence of a solution for the closed-loop system in the classical sense may not be guaranteed. To solve this problem, we employ a nonsmooth analysis technique including differential inclusion and Filippov solution. Through nonsmooth Lyapunov analysis, it is shown that uniformly bounded consensus results are derived and the bound of the consensus error is adjustable by choosing suitable design parameters.

Adaptive output feedback regulation for a class of nonlinear systems subject to input and output quantization

Abstract In this paper, we study the global stabilization problem for a class of uncertain nonlinear systems with unknown growth rate by output feedback. Both the output signal and the input signal of the system are quantized for the sake of less communication burden. To analyze the resulting discontinuous system, we adopt the non-smooth analysis techniques including the Filippov solution and differential inclusion. A new control law with an adaptive gain is proposed to compensate for the quantization errors. It is proved that the proposed scheme ensures that all the closed-loop signals are globally bounded. In addition, the output signal can be regulated to a bounded compact set which is explicitly given.

Adaptive compensation for actuator failures with event-triggered input

Abstract In this paper, we study the problem of event-triggered control for a class of uncertain nonlinear systems subject to actuator failures. The actuator failures are allowed to be unknown and the total number of failures could be infinite. To reduce the communication burden from the controller to the actuator, a novel event-triggered control law is designed. It is proved through Lyapunov analyses that the proposed control protocol ensures that all the signals of the closed-loop system are globally bounded and the system output tracking error can exponentially converge to a residual which can be made arbitrarily small.

Adaptive Backstepping Control for a Class of Nonlinear Systems With Non-Triangular Structural Uncertainties

In this technical note, a robust adaptive control scheme is proposed based on backstepping techniques for a class of nonlinear systems with unknown parameters. A modeling error may also exist in every state equation or channel and it is bounded by a known function which is allowed to depend on all system states. It is shown that the proposed adaptive control scheme can ensure all signals in the closed-loop system bounded, if the strength of system modeling errors is sufficiently weak. Transient performance is also established. Thus stabilizing systems in classical strict-feedback forms with sufficiently small non-triangular structural perturbations is successfully addressed. In the case that system parameters are known, a non-adaptive robust controller is designed to globally exponentially stabilize such a class of nonlinear systems. Finally simulation studies are used to verify the effectiveness of the proposed scheme.