A New Approach in Design of Sliding Mode Controller by Optimization State Feedback for Two Wheeled Self Balancing Robot

Abstract

The Two-Wheeled Self-Balancing mobile Robot (TWSBR) is one of the unstable highly nonlinear dynamic systems. This work aims to design a robust controller for controlling TWSBR, in order to solve the balancing and tracking problems. A Sliding Mode Controller based on state feedback (SFSMC) is suggested to solve these problems. In this work, the equivalent –like the term of the SMC’s control law is estimated using a state feedback in order to overcome the dependency of the SMC to the robot model and to reject undesirable effect of interaction toward the improvement of robustness. SFSMC parameters have been tuned using modified Cuckoo Search (MCS) and modified Particle Swarm Optimization (MPSO) algorithms to improve its performance in terms of processing time and response accuracy of the robot system. To measure the performance of the robot system, the Integral Square Error (ISE) has been used as a performance index. Simulation results show improvement in the performance of the TWSBR using SFSMC over the classic SMC in terms of processing time and tracking error.