Sharkawy, A. (2012). A COMPUTATIONALLY EFFICIENT FUZZY CONTROL SCHEME FOR A CLASS OF MIMO SYSTEMS: THE EXAMPLE OF ROBOT MANIPULATORS. JES. Journal of Engineering Sciences, 40(No 1), 147-171. doi: 10.21608/jesaun.2012.112723
Abdel Badie Sharkawy. "A COMPUTATIONALLY EFFICIENT FUZZY CONTROL SCHEME FOR A CLASS OF MIMO SYSTEMS: THE EXAMPLE OF ROBOT MANIPULATORS". JES. Journal of Engineering Sciences, 40, No 1, 2012, 147-171. doi: 10.21608/jesaun.2012.112723
Sharkawy, A. (2012). 'A COMPUTATIONALLY EFFICIENT FUZZY CONTROL SCHEME FOR A CLASS OF MIMO SYSTEMS: THE EXAMPLE OF ROBOT MANIPULATORS', JES. Journal of Engineering Sciences, 40(No 1), pp. 147-171. doi: 10.21608/jesaun.2012.112723
Sharkawy, A. A COMPUTATIONALLY EFFICIENT FUZZY CONTROL SCHEME FOR A CLASS OF MIMO SYSTEMS: THE EXAMPLE OF ROBOT MANIPULATORS. JES. Journal of Engineering Sciences, 2012; 40(No 1): 147-171. doi: 10.21608/jesaun.2012.112723
A COMPUTATIONALLY EFFICIENT FUZZY CONTROL SCHEME FOR A CLASS OF MIMO SYSTEMS: THE EXAMPLE OF ROBOT MANIPULATORS
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.