A suboptimal dual controller for stochastic systems with unknown parameters

In this paper a simple suboptimal dual controller is proposed which brings together Clarke and Gawthrop's (1975) self-tuning controller framework and a generalization of Milito's (Milito el at. 1982) innovations dual controller for a class of linear single-input single-output stochastic sy...

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Bibliographic Details
Published in:International journal of control 1985-01, Vol.41 (2), p.507-524
Main Authors: CHAN, S. S., ZARROP, M. B.
Format: Article
Language:English
Subjects:
Applied sciences
Computer science
control theory
systems
Control theory. Systems
controllers
economics
Exact sciences and technology
Optimal control
optimization
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Summary:In this paper a simple suboptimal dual controller is proposed which brings together Clarke and Gawthrop's (1975) self-tuning controller framework and a generalization of Milito's (Milito el at. 1982) innovations dual controller for a class of linear single-input single-output stochastic systems with unknown parameters. A cost function which includes the variances of both an auxiliary output and its prediction error is used to optimize the system performance. The latter variance term forces the controller to gather information to enhance parameter estimation and thus to indirectly improve control performance. Consequently the dual property inherent in optimal stochastic control is embedded in the structure of the suboptimal controller. Various interpretations and properties of the new algorithm are discussed. Comparative performances of the generalized minimum variance self-tuning controller and the suboptimal dual controller when applied to various simulated stochastic systems are examined. The. improvement of the performance of the new dual controller over self-tuning controllers in terms of transient behaviour and in coping with various time-varying parameter situations is substantial.
ISSN:0020-7179
1366-5820
DOI:10.1080/0020718508961143