Parameter Optimization Of Analytic Fuzzy Controllers For Robot Manipulators
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J. Kasac, B. Novakovic, D. Majetic & D. Brezak
An open question in fuzzy logic control of robot manipulators is how to modify the fuzzy controller parameters to guarantee appropriate performance specifications. In this paper a new approach to performance tuning of analytic fuzzy controllers for robot manipulators is presented. The analytic fuzzy control is a nonconventional approach that uses an analytic function for output determination, instead of a fuzzy rule base. The proposed approach is based on construction of a parameter dependent Lyapunov function. With the appropriate choice of the free parameter an estimation of the integral performance index is obtained. The estimated performance index depends on controller parameters and a few parameterswhich characterize the robot dynamics. The optimal values of the controller gains are obtained by minimization of the performance index. An example is given to demonstrate the obtained results. Keywords: parameters optimization, fuzzy control, robot control, performance evaluation, global stability, Lyapunov stability. 1 Introduction A significant problem in the conventional fuzzy logic control (FLC) is the exponential growth in rules as the number of variables increases. Consequently, the application of the conventional FLC to the multivariable systems like robots, in the process of the real-time control, becomes difficult. It becomes necessary to suggest ways to cope with a vexing problem in fuzzy logic: the exponential growth in rules as the number of variables increases . These problems have been avoided in [2, 3] by introducing a new, nonconventional analytic method for synthesis of the fuzzy robot control. For this purpose
parameters optimization, fuzzy control, robot control, performance evaluation, global stability, Lyapunov stability.