Decentralized fuzzy linguistic control of multiple robotic manipulators with guaranteed global
stability
Yongqing Fan | Xi’an University of Posts and Telecommunications
Wenqing Wang | Xi’an University of Posts and Telecommunications
Xiangkui Jiang | Xi’an University of Posts and Telecommunications
Zhen Li | Xi’an University of Posts and Telecommunications
A decentralized adaptive control based on human linguistic is investigated to learn human behaviors for multiple
robotic manipulators. Many experts’ words or sentences can be transferred into the control actions by employing membership
functions in robot systems, which can be synthesized fuzzy controller by employing reasoning mechanism. For the unknown model
dynamical robot manipulators, one adjustable parameter that relates to the approximation accuracy of fuzzy logic systems is
introduced at first, which be utilized to deal with the unknown dynamics of robot manipulators. Switching fuzzy adaptive
controller is designed to overcome the limitation of logic structure that the number of adaptive laws only focus on fuzzy rules in
conventional fuzzy logic systems. Another advantage of this design method is that the control with human linguistic extend the
semi-global stability to global stability. Finally, effectiveness of the developed control design scheme has been shown in
simulation example.
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