Title: Decoupling control in statistical sense: minimised mutual information algorithm

Authors: Qichun Zhang; Aiping Wang

Addresses: School of Electrical and Electronic Engineering, The University of Manchester, Manchester, M13 9PL, UK ' Institute of Computer Sciences, Anhui University, Hefei, China

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 independence; Cauchy-Schwarz mutual information; CSMI; information potential; NARMA models; compensation; controller design; stability analysis.

DOI: 10.1504/IJAMECHS.2016.082625

International Journal of Advanced Mechatronic Systems, 2016 Vol.7 No.2, pp.61 - 70

Received: 28 Mar 2016
Accepted: 15 Sep 2016
Published online: 03 Mar 2017 *

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