PSO-based H∞ Fuzzy Control of an Underactuated Robot Using Linear Matrix Inequality

Abstract

This research presents the H∞ fuzzy control of an underactuated robot using particle swarm optimization (PSO) algorithms with linear matrix inequalities (LMI) stability conditions. First, linearizing the underactuated robot at various operating points establishes the T-S fuzzy model and fuzzy rules. Then the LMI-based stability conditions are derived for the underactuated robot through Lyapunov theory such that the T-S fuzzy control systems possess H∞ performance against external disturbance. Moreover, the optimal T-S fuzzy control gains are explored by using PSO algorithms. Results demonstrate the proposed PSO-based H∞ fuzzy controller is superior to the existing LMI-based H∞ fuzzy controller.