Based on Genetic Algorithm and Input Estimation Approach to Design a Sliding Mode Controller for Flexible-Joint Robot Control System

Abstract

In this work, the genetic algorithm (GA) and input estimation approach (IE) are proposed to design a sliding mode controller (SMC) that hold ability of disturbance torque estimation and the robust control performance. The IE approach is an on-line recursive inverse estimation method based on the Kalman filter (KF) and recursive least square estimator method (RLSE), which estimates the disturbance torque without additional torque sensor. The sliding mode control theory has the characteristics of low sensitivity with variable system parameters. Furthermore, the genetic algorithm is proposed to search the optimal controller design parameters for SMC that it can promote the control performance.