Abstract
A methodology for the design of fuzzy control laws for tracking control of mechanical systems is described. The approach uses Lyapunov's stability theory to formulate a class of control laws that guarantee convergence of the tracking errors to within specification limits in presence of bounded parameter uncertainties and input disturbances. The proposed methodology results in control laws that possess a large number of parameters and functional relationships to be chosen by the designer. The flexibility of the approach makes it suitable for fuzzy logic implementation. Different fuzzy implementations of the proposed control methodology are described. All implementations guarantee tracking error convergence to within prespecified performance limits. Simulations using a model of a two-degree-of-freedom robot manipulator were performed to investigate fuzzy and non-fuzzy implementations of the proposed methodology. The study demonstrates better performance of the fuzzy control implementation compared to its non-fuzzy counterpart.
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