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Iterative minimization of H2 control performance criteria

Date

2008

Authors

Bazanella, Alexandre
Gevers, Michel
Miskovic, Ljubisa
Anderson, Brian

Journal Title

Journal ISSN

Volume Title

Publisher

Pergamon-Elsevier Ltd

Abstract

Data-based control design methods most often consist of iterative adjustment of the controller's parameters towards the parameter values which minimize an H2 performance criterion. Typically, batches of input-output data collected from the system are used to feed directly a gradient descent optimization - no process model is used. A limiting factor in the application of these methods is the lack of useful conditions guaranteeing convergence to the global minimum; several adaptive control algorithms suffer from the same limitation. In this paper the H2 performance criterion is analyzed in order to characterize and enlarge the set of initial parameter values from which a gradient descent algorithm can converge to its global minimum.

Description

Keywords

Keywords: Control design methods; Data-based control design; H 2 performance criteria; Parameter values; Iterative methods Data-based control design; H2 performance criteria

Citation

Source

Automatica

Type

Journal article

Book Title

Entity type

Access Statement

License Rights

DOI

10.1016/j.automatica.2008.03.014

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