Trajectory tracking of Maryland manipulator using linguistic Lyapunov fuzzy controller

Stability of a parallel manipulator is a very important issue due to its high nonlinearity and vague dynamics. This problem may be overcome by a controller, based on the combination of Lyapunov theory and fuzzy logic. In this paper a novel linguistic Lyapunov based fuzzy controller (LLFC) is proposed in which fuzzy logic controller improves trajectory tracking performance of parallel manipulator and application of Lyapunov theory provides stable control action. The subsequent part of rule base in fuzzy controller is constrained by Lyapunov criteria so as to generate a control action which stabilizes the system. Non dominated sorting genetic algorithm-II (NSGA-II) optimization technique is used to evaluate the optimal values of controller parameters. The effectiveness of proposed LLFC controller is tested on Maryland manipulator and compared with PID, Fractional order PID (FOPID) and Fractional order fuzzy pre-compensated fractional order PID (FOFP FOPID) controllers. Simulation results reveal that the proposed controller shows stable, robust and better tracking performance for Maryland manipulator in comparison to PID, FOPID and FOFP FOPID controllers.