Weiqing Ai

Universal adaptive regulation for a class of nonlinear systems with unknown time delays and output function via output feedback

Abstract This paper investigates the adaptive output feedback control problem for a class of nonlinear systems with unknown time delays and output function. The system satisfies linear growth condition with an unknown growth rate. First of all, based on a dynamic gain scaling technique, we present a new dynamic high-gain observer without requiring precise information of the output function. Then, by employing the idea of universal control and the backstepping method, a universal adaptive output feedback control law is designed to globally regulate all the states of the system. A simulation example is presented to illustrate the effectiveness of the proposed design scheme.

Finite-time state-feedback control for a class of stochastic high-order nonlinear systems

This paper discusses the problem of global finite-time stabilization in probability for a class of stochastic high-order nonlinear systems whose drift and diffusion terms satisfy lower-triangular growth conditions. By adopting adding one power integrator technique and constructing twice continuous differential Lyapunov functions, a continuous state-feedback controller is recursively designed. Based on stochastic finite-time stability theorem, it is proved that the solution of the closed-loop system is finite-time stable in probability. Several simulation examples are given to illustrate the effectiveness of the proposed design procedure.

Disturbance observer-based robust control for trajectory tracking of wheeled mobile robots

This paper proposes an adaptive controller for the trajectory tracking of a nonholonomic wheeled mobile robot with nonholonomic constraints in the presence of external disturbances and unknown parameters. A new scheme is proposed to design an adaptive virtual velocity controller and torque control law. Meanwhile, a disturbance observer is applied to estimate the lumped disturbance to achieve the feedforward compensation. Simulation results demonstrate the effectiveness of the proposed control scheme.

Global practical tracking for a class of uncertain nonlinear systems via sampled-data control

This paper investigates the problem of global practical tracking via sampled-data output feedback for a class of uncertain nonlinear systems whose output functions are not precisely known. To solve the problem, we first construct a new sampled-data compensator and then use the backstepping and output feedback domination approach to design a linear sampled-data controller. An explicit formula for the sampling period is computed to regulate the tracking error under the proposed controller with appropriate gains. A practical example is given to illustrate the effectiveness of the proposed scheme.

Decentralized global output feedback stabilization for a class of uncertain nonlinear systems

This paper considers the problem of decentralized global stabilization via output feedback for a class of uncertain nonlinear systems with unknown output functions, in which the nonlinear terms are interconnected by unmeasurable states and the inputs of each subsystem. First, we design the controller for each nominal subsystem without the perturbing nonlinearities. Then, we apply the homogeneous domination approach to design scaled homogeneous observers and controllers with an appropriate choice of gain to render the nonlinear system globally asymptotically stable. Finally, two simulation examples are shown to illustrate the effectiveness of the proposed scheme.

Global output feedback stabilization for a class of stochastic feedforward nonlinear systems with time-varying input delay:

This paper investigates the problem of output feedback stabilization for a class of stochastic feedforward nonlinear systems with time-varying input delay. The drift and diffusion terms satisfy the linear growth condition and are dependent on unmeasurable states and the delayed input. First, we use a change of coordinates to introduce a scaling gain into the system. Then, based on the high-gain observer technique, a delay-free output feedback controller with the scaling gain is developed. Based on the Lyapunov–Krasovskii method and the idea of feedback domination, it is shown that the closed-loop system can be rendered globally asymptotically stable in probability via appropriately choosing the scaling gain. Finally, two examples are presented to illustrate the effectiveness of the proposed scheme.

Decentralized output feedback stabilization of large-scale uncertain nonlinear systems

This paper addresses the problem of decentralized global stabilization by output feedback for a class of uncertain large-scale nonlinear systems. A new design method based on the homogeneous domination approach and finite-time stabilization technique is developed, which leads to global output feedback stabilization for large-scale uncertain nonlinear systems under a homogeneous growth condition. Firstly, a homogeneous observer and controller is constructed for the nominal system without the perturbing nonlinearities for each subsystem. Then, a scaling gain is introduced into the homogeneous observers and controllers to globally stabilize the uncertain nonlinear systems.

Global control for a class of planar stochastic nonlinear systems with unknown output gain

This paper addresses the problem of global asymptotical stabilization via output feedback for a class of planar stochastic nonlinear systems whose output gain is not precisely known. We first design an observer and use the estimated states to construct a controller to globally stabilize the nominal linear system without considering perturbing nonlinearities. Then we apply the homogeneous domination approach to design a homogeneous observer and controller with an appropriate choice of scaling gain to render the planar stochastic nonlinear system globally asymptotically stable in probability.