Sliding-mode neuro-controller for uncertain systems

Yıldız, Yıldıray and Şabanoviç, Asif and Abidi, Khalid Seyed (2007) Sliding-mode neuro-controller for uncertain systems. IEEE Transactions on Industrial Electronics, 54 (3). pp. 1676-1685. ISSN 0278-0046

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Abstract

In this paper, a method that allows for the merger of the good features of sliding-mode control and neural network (NN) design is presented. Design is performed by applying an NN to minimize the cost function that is selected to depend on the distance from the sliding-mode manifold, thus providing that the NN controller enforces sliding-mode motion in a closed-loop system. It has been proven that the selected cost function has no local minima in controller parameter space, so under certain conditions, selection of the NN weights guarantees that the global minimum is reached, and then the sliding-mode conditions are satisfied; thus, closed-loop motion is robust against parameter changes and disturbances. For controller design, the system states and the nominal value of the control input matrix are used. The design for both multiple-input-multiple-output and single-input-single-output systems is discussed. Due to the structure of the (M)ADALINE network used in control calculation, the proposed algorithm can also be interpreted as a sliding-mode-based control parameter adaptation scheme. The controller performance is verified by experimental results.
Item Type: Article
Uncontrolled Keywords: neural networks (NNs); sliding-mode control (SMC)
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Asif Şabanoviç
Date Deposited: 04 Dec 2006 02:00
Last Modified: 04 Sep 2019 11:00
URI: https://research.sabanciuniv.edu/id/eprint/76

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