Sliding mode control parameter tuning using ant colony optimization for a 2-DOF hydraulic servo system

Abstract

A tuning mechanism for a sliding mode controller (SMC) used for a 2-DOF hydraulic servo system is proposed. In this paper we aim to develop techniques for optimally tuning the SMC parameters for a system that tracks the vertical displacement and angular orientation of the parallel manipulator. We propose an ant colony optimization (ACO) algorithm to tune four SMC parameters. The performance of ACO is compared to the manually-tuned and genetic algorithm (GA)-tuned SMC. The results from simulation showed that the ACO-SMC performance is comparable to that of GA-SMC, for tracking the heave and the pitch of the system when evaluating tracking error and the actuator action required. The GA-SMC exhibits high frequency chattering, while the ACO-SMC does not. From the simulated results we conclude that, overall, the application of ACO to SMC parameter tuning improves the systems performance.