On possibilities of the practical implementation of balance-based adaptive control methodology
Jacek Czeczot (2007)
Control and Cybernetics
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Jacek Czeczot (2007)
Control and Cybernetics
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Shuping Tan, Ji-Feng Zhang (2009)
ESAIM: Control, Optimisation and Calculus of Variations
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This paper is concerned with the sampled-data based adaptive linear quadratic (LQ) control of hybrid systems with both unmeasurable Markov jump processes and stochastic noises. By the least matching error estimation algorithm, parameter estimates are presented. By a double-step (DS) sampling approach and the certainty equivalence principle, a sampled-data based adaptive LQ control is designed. The DS-approach is characterized by a comparatively large estimation step for parameter estimation...
Bernard Frankpitt, John S. Baras (1998)
Kybernetika
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This paper provides a summary of our recent work on the problem of combined estimation and control of systems described by finite state, hidden Markov models. We establish the stochastic framework for the problem, formulate a separated control policy with risk-sensitive cost functional, describe an estimation scheme for the parameters of the hidden Markov model that describes the plant, and finally indicate how the combined estimation and control problem can be re-formulated in a framework...
Jaroslav Markl (1985)
Kybernetika
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Dariusz Janczak, Yuri Grishin (2006)
Control and Cybernetics
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V. Borkar, S. Associate (1998)
Applicationes Mathematicae
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This paper considers Bayesian parameter estimation and an associated adaptive control scheme for controlled Markov chains and diffusions with time-averaged cost. Asymptotic behaviour of the posterior law of the parameter given the observed trajectory is analyzed. This analysis suggests a "cost-biased" estimation scheme and associated self-tuning adaptive control. This is shown to be asymptotically optimal in the almost sure sense.