A COMPUTATIONALLY EFFICIENT FUZZY CONTROL SCHEME FOR A CLASS OF MIMO SYSTEMS: THE EXAMPLE OF ROBOT MANIPULATORS

Document Type : Research Paper

Author

Associate Professor, Mechanical Engineering Department, Faculty of Engineering, Assiut University, 71516, EGYPT

Abstract

This paper develops a decentralized fuzzy control scheme for MIMO nonlinear second order systems with application to robot manipulators via a combination of genetic algorithm and fuzzy systems. The controller for each joint consists of a feedforward fuzzy torque-computing system and a feedback fuzzy PD system. The feedforward fuzzy system is trained and optimized off-line by an improved genetic algorithm, that is to say, not only the parameters but also the structure of the fuzzy system is self-organized. The feedback fuzzy PD system, on the other hand, is used to keep the closed-loop stable. The rule base consists of only four rules per each degree of freedom (DOF). Furthermore, the fuzzy feedback system is decentralized and simplified leading to a computationally efficient control scheme. The proposed control scheme has the following merits: 1) it needs no exact dynamics of the system and the computation is time-saving because of the simple structure of the fuzzy systems; and 2) the controller is insensitive to various parameters and payload uncertainties. These are demonstrated by analysis of the computational complexity and various computer simulations.

Keywords

Main Subjects

JES. Journal of Engineering Sciences
Volume 40, No 1
January and February 2012
Pages 147-171

Files

Share

How to cite

Statistics