A COMPUTATIONALLY EFFICIENT FUZZY CONTROL SCHEME FOR A CLASS OF MIMO SYSTEMS: THE EXAMPLE OF ROBOT MANIPULATORS | ||||
| JES. Journal of Engineering Sciences | ||||
| Article 9, Volume 40, No 1, January and February 2012, Page 147-171 PDF (565.16 K) | ||||
| Document Type: Research Paper | ||||
| DOI: 10.21608/jesaun.2012.112723 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Abdel Badie Sharkawy | ||||
| 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 | ||||
| Robot manipulators; Genetic algorithm; Feedforward fuzzy torque computing; Fuzzy PD feedback control; Closed-loop stability; Computational complexity; Parametric and payload uncertainties | ||||
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