Fractional-Order Multivariable Adaptive Control Based on a Nonlinear Scalar Update Law

Fang Yan, Xiaorong Hou () and Tingting Tian
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Fang Yan: School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Xiaorong Hou: School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Tingting Tian: School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Mathematics, 2022, vol. 10, issue 18, 1-13

Abstract: This paper proposes a new fractional-order model reference adaptive control (FOMRAC) framework for a fractional-order multivariable system with parameter uncertainty. The designed FOMRAC scheme depends on a fractional-order nonlinear scalar update law. Specifically, the scalar update law does not change as the input–output dimension changes. The main advantage of the proposed adaptive controller is that only one parameter online update is needed such that the computational burden in the existing FOMRAC can be relieved. Furthermore, we show that all signals in this adaptive scheme are bounded and the mean value of the squared norm of the error converges to zero. Two illustrative numerical examples are presented to demonstrate the efficiency of the proposed control scheme.

Keywords: fractional-order model reference adaptive control (FOMRAC); multivariable; fractional-order nonlinear scalar update law; stability analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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