Displaying similar documents to “Double-stepped adaptive control for hybrid systems with unknown Markov jumps and stochastic noises”

On adaptive control for the continuous time-varying JLQG problem

Adam Czornik, Andrzej Świernik (2005)

International Journal of Applied Mathematics and Computer Science

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In this paper the adaptive control problem for a continuous infinite time-varying stochastic control system with jumps in parameters and quadratic cost is investigated. It is assumed that the unknown coefficients of the system have limits as time tends to infinity and the boundary system is absolutely observable and stabilizable. Under these assumptions it is shown that the optimal value of the quadratic cost can be reached based only on the values of these limits, which, in turn, can...

Double-stepped adaptive control for hybrid systems with unknown Markov jumps and stochastic noises

Shuping Tan, Ji-Feng Zhang (2008)

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...

Approximation and estimation in Markov control processes under a discounted criterion

J. Adolfo Minjárez-Sosa (2004)

Kybernetika

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We consider a class of discrete-time Markov control processes with Borel state and action spaces, and ℜ k -valued i.i.d. disturbances with unknown density ρ . Supposing possibly unbounded costs, we combine suitable density estimation methods of ρ with approximation procedures of the optimal cost function, to show the existence of a sequence { f ^ t } of minimizers converging to an optimal stationary policy f ∞ .