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Abstract

The robot manipulators are highly nonlinear, time varying and one of the important challenges in the field of robotics is the effective control of manipulators. This paper presents a technique to extract the rules of Fuzzy Logic Computed Torque Controller for PUMA-560 robot arm with uncertainties. Fuzzy Logic Controllers are placed at the input of the PD Controller to make the gains adaptive. Prisoner’s dilemma is employed to systematically tune the gains of the controller. The interrelations between inputs and outputs of a Fuzzy Linguistic Model are assigned using payoff matrix through Prisoner’s Dilemma. The difficulty in designing of fuzzy controllers is the extraction of the rule base. The extraction of fuzzy control rules requires good understanding of the plant and control theory. The present paper utilizes Fuzzy Lyapunov Synthesis to constitute the rule base assuming that minimal knowledge about the plant to be controlled. Simulation results prove the effective performance of the proposed controller in minimizing the error in joint angles when compared to Proportional Derivative Computed Torque Controller (PD-CTC), normal Fuzzy Logic Controller (FLC) and that of the reference signal.

Keywords

PUMA-560 robot manipulator fuzzy controller Prisoner’s dilemma Lyapunov synthesis

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Design of Prisoner’s dilemma based fuzzy logic computed torque controller with Lyapunov synthesis linguistic model for PUMA-560 robot manipulator

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