An analytical fuzzy-based approach to -gain optimal control of input-affine nonlinear systems using Newton-type algorithm.

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Bibliographic Details
Title: An analytical fuzzy-based approach to -gain optimal control of input-affine nonlinear systems using Newton-type algorithm.
Authors: Milic, Vladimir1, Kasac, Josip1, Novakovic, Branko1
Source: International Journal of Systems Science. Oct2015, Vol. 46 Issue 13, p2448-2460. 13p.
Subjects: Fuzzy logic, Nonlinear systems, Mathematical optimization, Weierstrass-Stone theorem, Approximation theory
Abstract: This paper is concerned with-gain optimisation of input-affine nonlinear systems controlled by analytic fuzzy logic system. Unlike the conventional fuzzy-based strategies, the non-conventional analytic fuzzy control method does not require an explicit fuzzy rule base. As the first contribution of this paper, we prove, by using the Stone–Weierstrass theorem, that the proposed fuzzy system without rule base is universal approximator. The second contribution of this paper is an algorithm for solving a finite-horizon minimax problem for-gain optimisation. The proposed algorithm consists of recursive chain rule for first- and second-order derivatives, Newton’s method, multi-step Adams method and automatic differentiation. Finally, the results of this paper are evaluated on a second-order nonlinear system. [ABSTRACT FROM PUBLISHER]
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Database: Engineering Source
Description
Abstract:This paper is concerned with-gain optimisation of input-affine nonlinear systems controlled by analytic fuzzy logic system. Unlike the conventional fuzzy-based strategies, the non-conventional analytic fuzzy control method does not require an explicit fuzzy rule base. As the first contribution of this paper, we prove, by using the Stone–Weierstrass theorem, that the proposed fuzzy system without rule base is universal approximator. The second contribution of this paper is an algorithm for solving a finite-horizon minimax problem for-gain optimisation. The proposed algorithm consists of recursive chain rule for first- and second-order derivatives, Newton’s method, multi-step Adams method and automatic differentiation. Finally, the results of this paper are evaluated on a second-order nonlinear system. [ABSTRACT FROM PUBLISHER]
ISSN:00207721
DOI:10.1080/00207721.2013.860640