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Cautious hierarchical switching control of stochastic linear systems
Author(s) -
Campi M.C.,
Hespanha João P.,
Prandini Maria
Publication year - 2004
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.797
Subject(s) - supervisor , robustness (evolution) , computer science , control theory (sociology) , supervisory control , equivalence (formal languages) , mathematics , control (management) , artificial intelligence , biochemistry , chemistry , discrete mathematics , political science , law , gene
Standard switching control methods are based on the certainty equivalence philosophy in that, at each switching time, the supervisor selects the candidate controller that is better tuned to the currently estimated process model. In this paper, we propose a new supervisory switching logic that takes into account the uncertainty on the process description when performing the controller selection. Specifically, a probability measure describing the likelihood of the different models is computed on‐line based on the collected data and, at each switching time, the supervisor selects the candidate controller that, according to this probability measure, performs the best on the average. If the candidate controller class is hierarchically structured so that for each model one has available several controllers with distinct levels of robustness, the supervisor automatically selects the controller that suitably compromises robustness versus performance, given the current level of model uncertainty. The use of randomized algorithms makes the supervisor implementation computationally tractable. Copyright © 2004 John Wiley & Sons, Ltd.