Adaptive Sliding Mode Control for a Hydraulic Position Servo System

Abstract

AbstractThe electro-hydraulic system is a typical complex system with nonlinear and high-order characteristics, which could seriously restrict the application of many advanced control algorithms. In this study, a sliding mode controller (SMC) based on adaptive neural network is proposed for a hydraulic position servo system with nonlinearity and parameter uncertainties. Structure design of a rotary hydraulic actuator is first introduced, and mathematical model of the hydraulic position servo system is constructed based on dynamic characteristics of the servo valve and the liquid flow continuity equation. Next, the adaptive neural network algorithm and sliding mode control technique are effectively combined to realize that the position signal of the hydraulic joint can be tracked along the desired command quickly and effectively. The SMC is adopted for its robustness against the uncertainty and nonlinearity of the target system, whereas the higher-order neural network observer is utilized to compensate parametric uncertainties to improve the accuracy. In addition, the closed-loop asymptotic stability of the designed control strategy is guaranteed by employing the Lyapunov theory. To investigate the tracking performance of the proposed controller, numerical simulation experiments have carried out and the results demonstrated the effectiveness of proposed control scheme.KeywordsElectro-hydraulic systemParameter uncertaintiesSliding mode controllerHigh-order neural network