Fuzzy-Basis-Function-Network-Based $H_\infty$ Tracking Control for Robotic Manipulators Using Only Position Feedback

摘要

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper presents an <formula formulatype="inline"><tex Notation="TeX">$H_\infty$</tex></formula> 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 <formula formulatype="inline"><tex Notation="TeX">$H_\infty$</tex></formula> 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 <formula formulatype="inline"><tex Notation="TeX">$H_\infty$</tex></formula> FBFN-based output-feedback control approach. </para>