Weichao Sun

Disturbance Observer-Based Adaptive Tracking Control With Actuator Saturation and Its Application

This paper is concerned with the problem of adaptive tracking control for a class of nonlinear systems with parametric uncertainty, bounded external disturbance, and actuator saturation. In order to achieve robust output tracking for the saturated uncertain nonlinear systems, a combination of adaptive robust control (ARC) and a novel terminal sliding-mode-based nonlinear disturbance observer (TSDO) is proposed, where the modeling inaccuracy and disturbance are integrated as a lumped disturbance. Specifically, the observer errors of estimating the lump disturbances converge to zero in finite-time for improving the precision of estimation. The estimated disturbances are then used in the controller to compensate for the systems lumped disturbances. The analytical results show that the proposed scheme is stable and can guarantee the asymptotic tracking with the tracking error converging to zero even in the presence of disturbances. Finally, the developed method is illustrated the effectiveness by the application to control of a quarter-car model with active suspension system.

A Bioinspired Dynamics-Based Adaptive Tracking Control for Nonlinear Suspension Systems

This paper investigates the energy-efficiency design of adaptive control for active suspension systems with a bioinspired nonlinearity approach. To this aim, a bioinspired dynamics-based adaptive tracking control is proposed for nonlinear suspension systems. In many existing techniques, one important effort is used for canceling vibration energy transmitted by suspension inherent nonlinearity to improve ride comfort. Unlike existing methods, the proposed approach takes full advantage of beneficial nonlinear stiffness and damping characteristics inspired by the limb motion dynamics of biological systems to achieve advantageous nonlinear suspension properties with potentially less energy consumption. The stability analysis of the desired bioinspired nonlinear dynamics is conducted within the Lyapunov framework. Theoretical analysis and simulation results reveal that the proposed bioinspired nonlinear dynamics-based adaptive controller has a significant impact on the amount of energy consumption, considering the same basic control method and random excitation of road irregularity for a similar ride comfort performance.

Adaptive tracking control for stochastic mechanical systems with actuator nonlinearities

Abstract In this paper, output tracking control problem is investigated for a class of uncertain nonlinear random mechanical systems subjected to unknown actuator nonlinearities. Two common kinds of actuator nonlinearities, namely, Bouc–Wen hysteresis and dead-zone, are considered in a unified framework, such that the designed adaptive control law is robust to the mentioned actuator nonlinearities (hysteresis and dead-zone). Different from some existing controller design approaches for nonlinear systems with actuator nonlinearities, the usual priori knowledge on the known compact set for system uncertain parameters has been eliminated with the proposed control method. The proposed control law can ensure that the system output tracking error eventually converges to an arbitrarily small neighborhood of zero in the sense of mean square by turning controller gains. Simulation studies are performed to demonstrate the effectiveness of the proposed controller design approach.