Super Twisting Sliding Mode Controller for Trajectory Tracking Control of Autonomous Ground Vehicle System

Abstract

Day to day increase in demand of safe and accident free ground vehicle, rapid growth and development of artificial intelligence algorithms and also rapid growth of microelectronics technology are major motives that are driving the development and increased attention of Autonomous Ground Vehicle (AGV) systems. Unstable and non-linear features of AGV need robust control techniques to control the trajectory tracking tasks of the system. Review of related works summery shows that sliding mode controller can handle non-linearity and relatively assure robustness of the system. However; ripple is one of the most common challenge in sliding mode controllers. In this research, Super Twisting Sliding Mode controller (STSMC) is designed to resolve the ripple in sliding mode controller for trajectory tracking control of AGV. Optimal parameters of STSMC controller are tuned using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) technique. To compare the performance of the proposed algorithm, GA tuned Fractional-Order-PID (FOPID) controller is also designed and implemented. Accordingly, STSMC has less (≈0.0006 s) tracking error than FOPID controller. The result reveals the outperformance of the proposed algorithm over FOPID controller.