Adaptive Fuzzy Control for a SISO Nonlinear System
Hugang Han*, and Shuta Murakami**
*School of Business, Hiroshima Prefectural University, Shobara, Hiroshima 727-0023, Japan
**Faculty of Engineering, Kyushu Institute of Technology, Kitakyushu, Fukuoka 804-8550, Japan
When using the Lyapunov synthesis approach to construct an adaptive fuzzy control system, one important way is to regard the fuzzy systems as approximators to approximate the unknown functions in the system to be controlled. Concerning the unknownness, generally there are two cases: a completely unknown case, and a partly unknown case. However, most of the schemes presented so far have only focused on the former. Clearly, if an unknown function belongs to the latter, the knowledge available about the function should be utilized as much as possible in the development of the control system. In this paper, our goal is to design an adaptive fuzzy controller for a class of nonlinear systems with uncertainty, which can correspond to the either case. Also, we propose a unique way to deal with the uncertainty, i.e., adopt a switching function with an alterable coefficient, which is tuned by adaptive law based on the tracking error.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 International License.