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Perfect tracking control of discrete-time quadratic TS fuzzy systems via feedback linearisation

Xiaojun Ban, Liwei Ren, Zhibin Yan, Hao Ying

Year
2019
Citations
3

Abstract

Perfect tracking control is an important and frequently encountered requirement in various industries (e.g. robotic control). We developed a novel systematic framework for designing a fuzzy controller via feedback linearisation to control a class of discrete-time Takagi–Sugeno (TS) fuzzy systems with quadratic rule consequents to achieve such tracking. We established a necessary condition for its local stability and a necessary and sufficient condition for the boundedness of the controller. The feedback linearisation is known to fail to work in certain systems due to the unboundedness of the tracking controller output. To address this issue, we developed a method to check whether any given quadratic TS fuzzy system will cause such a failure. We developed a scheme to ensure that the output of the controller designed for any failure-causing system will be bounded and the resulting controller will attain nearly perfect tracking performance. Applying feedback linearisation to the quadratic fuzzy systems is innovative relative to the literature exclusively dealing with the TS fuzzy systems with linear rule consequents (including our previous results), which are now generalised by the new findings. Two numerical examples are provided to illustrate the effectiveness and utility of our new theoretical results.

Keywords

Control theory (sociology)Fuzzy logicController (irrigation)Fuzzy control systemQuadratic equationStability (learning theory)Bounded functionComputer scienceControl (management)Mathematics

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