Fuzzy-basis-function-network-based H∞ tracking control for robotic manipulators using only position feedback

Authors:
Chuan-Kai Lin
Affiliations:
Department of Electrical Engineering, Chinese Naval Academy, Kaohsiung, Taiwan
Venue:
IEEE Transactions on Fuzzy Systems
Year:
2009

Citing 16
Cited 1

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Abstract

This paper presents an H∞ fuzzy output-feedback tracking-control scheme for robotic manipulators without measuring joint velocities. The developed controller and observer are based on a fuzzy basis function network (FBFN), which is employed to approximate nonlinear functions in the dynamics of controller and observer. The FBFN-based observer that estimates joint velocities can remove the needs of full-state measurements. According to the inevitable approximation errors and external disturbances, an H∞ auxiliary control signal is used to suppress the effects of the uncertainties. Moreover, all parameters of the fuzzy basis functions (FBFs) and FBF-to-output weights can be tuned online. The proposed controller requires no prior knowledge about the dynamics of the robot manipulator and no offline learning phase. Finally, comparative simulations on a three-link robot manipulator are provided to illustrate the tracking performance of the H∞ FBFN-based output-feedback control approach.