Title: Neural networks-based adaptive robust controllers and its applications to water pollution control systems

Authors: Yuchao Wang; Hansheng Wu

Addresses: Graduate School of Comprehensive Scientific Research, Prefectural University of Hiroshima, Hiroshima City, Hiroshima 734-8558, Japan ' Department of Information Science, Prefectural University of Hiroshima, Hiroshima City, Hiroshima 734-8558, Japan

Abstract: The problem of robust stabilisation of uncertain dynamical systems with non-linear state perturbations is considered. In this paper, the neural networks (NNs) is used to approximate the unknown system dynamics to be a special form, and an adaptation law is employed to estimate the norm of the NNs weight and approximation error. By making use of the updated values of the norm of weight and approximation error, an adaptive robust state feedback control scheme is proposed for such a class of uncertain non-linear systems. It is also shown that by employing the proposed adaptive robust controllers, the state trajectories of uncertain non-linear systems can be guaranteed to be uniformly ultimately bounded. Finally, to demonstrate the validity of the result, we apply it to solve a practical problem of water pollution.

Keywords: adaptive control; neural networks; uncertain nonlinear systems; robust stability; uniform ultimate boundedness; water pollution control; water quality; robust control; system dynamics; feedback control.

DOI: 10.1504/IJAMECHS.2013.055990

International Journal of Advanced Mechatronic Systems, 2013 Vol.5 No.2, pp.138 - 145

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 23 Aug 2013 *

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