Design of Intelligent Hybrid Controller for a Robot with Uncertain Parameters

Abstract

This paper presents an intelligent hybrid control system for controlling the position and orientation of a robot with uncertain parameters. Due to the nonlinear and time varying dynamics, parameter uncertainties, and the existence of uncertain disturbances, a sliding-mode controller (SMC) combined with fuzzy logic controller is proposed. In this way, the switching function is introduced as a corrective controller for removing chattering, which is used by the fuzzy controller to adjust the slope of the switching function. In this proposed control approach, the time delay estimation method (TDE) has been utilized to reduce the uncertainties of the control law and the genetic algorithm (GA) has also been employed to optimize the controller parameters. In order to evaluate the efficiency of the proposed control system, we compare the proposed controller with sliding-mode controller optimized with genetic algorithm (SMC-GA) and sliding-mode controller using TDE (SMC-TDE) to control the position and orientation. The simulation results show that the fuzzy sliding-mode controller using TDE and GA (fuzzy SMC-TDE-GA) successfully control a robot with 6 degree of freedom (6-DOF) in 3-D space.