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An Efficient Adaptive Fuzzy Control Scheme for Industrial Manipulators

Abdel Badie Sharkawy, Douglas A. Plaza, and Daniel E. Ochoa
Escuela Superior Politécnica del Litoral, ESPOL, Guayaquil, Ecuador
Abstract—This paper develops a generalized adaptive fuzzy control scheme for MIMO nonlinear second order systems. Here, the example robotic manipulators is used to illustrate the control algorithm. The controller for each degree of freedom (DOF) consists of a feedback fuzzy PD systems used to keep the closed-loop stable. The rule base consists of only four rules per each DOF. Furthermore, the fuzzy feedback system is decentralized and simplified leading to a computationally efficient control scheme. The proposed control scheme has the following advantages: 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 robust against various uncertainties. The computational complexity of the proposed control scheme has been analyzed and compared with previous works. Computer simulations show that this controller is effective in achieving the control goals.

Index Terms—robot manipulators, fuzzy pd feedback control, closed-loop stability, computational complexity

Cite: Abdel Badie Sharkawy, Douglas A. Plaza, and Daniel E. Ochoa, "An Efficient Adaptive Fuzzy Control Scheme for Industrial Manipulators," Jounal of Automation and Control Engineering, Vol. 4, No. 3, pp. 213-219, June, 2016. doi: 10.18178/joace.4.3.213-219
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