Performance-oriented antiwindup for a class of linear control systems with augmented neural network controller

Herrmann, Guido, Turner, Matthew and Postlethwaite, Ian (2007) Performance-oriented antiwindup for a class of linear control systems with augmented neural network controller. IEEE Transactions on Neural Networks, 18 (2). pp. 449-465. ISSN 1045-9227

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Abstract

This paper presents a conditioning scheme for a linear control system which is enhanced by a neural network (NN) controller and subjected to a control signal amplitude limit. The NN controller improves the performance of the linear control system by directly estimating an actuator-matched, unmodeled, nonlinear disturbance, in closed-loop, and compensating for it. As disturbances are generally known to be bounded, the nominal NN-control element is modified to keep its output below the disturbance bound. The linear control element is conditioned by an antiwindup (AW) compensator which ensures performance close to the nominal controller and swift recovery from saturation. For this, the AW compensator proposed is of low order, designed using convex linear matrix inequalities (LMIs) optimization.

Item Type:	Article
Uncontrolled Keywords:	control signal saturation, convex linear matrix inequalities
Subjects:	H600 Electronic and Electrical Engineering
Department:	Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User:	Sarah Howells
Date Deposited:	14 Nov 2012 14:51
Last Modified:	13 Oct 2019 00:23
URI:	http://nrl.northumbria.ac.uk/id/eprint/10228

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