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Decoupling control in statistical sense: minimised mutual information algorithm

Decoupling control in statistical sense: minimised mutual information algorithm This paper presents a novel concept to describe the couplings among the outputs of the stochastic systems which are represented by NARMA models. Compared with the traditional coupling description, the presented concept can be considered as an extension using statistical independence theory. Based on this concept, the decoupling control in statistical sense is established with the necessary and sufficient conditions for complete decoupling. Since the complete decoupling is difficult to achieve, a control algorithm has been developed using the Cauchy-Schwarz mutual information criterion. Without modifying the existing control loop, this algorithm supplies a compensative controller to minimise the statistical couplings of the system outputs and the local stability has been analysed. In addition, a further discussion illustrates the combination of the presented control algorithm and data-based mutual information estimation. Finally, a numerical example is given to show the feasibility and efficiency of the proposed algorithm. Keywords: nonlinear stochastic systems; decoupling control; statistical sense; statistical independence; Cauchy-Schwarz mutual information; CSMI; information potential. Reference to this paper should be made as follows: Zhang, Q. and Wang, A. (2016) `Decoupling control in statistical sense: minimised mutual information algorithm', Int. J. Advanced Mechatronic Systems, Vol. 7, No. 2, pp.61­70. Biographical notes: Qichun http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Advanced Mechatronic Systems Inderscience Publishers

Decoupling control in statistical sense: minimised mutual information algorithm

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Publisher
Inderscience Publishers
Copyright
Copyright © 2016 Inderscience Enterprises Ltd.
ISSN
1756-8412
eISSN
1756-8420
DOI
10.1504/IJAMECHS.2016.082625
Publisher site
See Article on Publisher Site

Abstract

This paper presents a novel concept to describe the couplings among the outputs of the stochastic systems which are represented by NARMA models. Compared with the traditional coupling description, the presented concept can be considered as an extension using statistical independence theory. Based on this concept, the decoupling control in statistical sense is established with the necessary and sufficient conditions for complete decoupling. Since the complete decoupling is difficult to achieve, a control algorithm has been developed using the Cauchy-Schwarz mutual information criterion. Without modifying the existing control loop, this algorithm supplies a compensative controller to minimise the statistical couplings of the system outputs and the local stability has been analysed. In addition, a further discussion illustrates the combination of the presented control algorithm and data-based mutual information estimation. Finally, a numerical example is given to show the feasibility and efficiency of the proposed algorithm. Keywords: nonlinear stochastic systems; decoupling control; statistical sense; statistical independence; Cauchy-Schwarz mutual information; CSMI; information potential. Reference to this paper should be made as follows: Zhang, Q. and Wang, A. (2016) `Decoupling control in statistical sense: minimised mutual information algorithm', Int. J. Advanced Mechatronic Systems, Vol. 7, No. 2, pp.61­70. Biographical notes: Qichun

Journal

International Journal of Advanced Mechatronic Systems – Inderscience Publishers

Published: Jan 1, 2016

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