Výzkumná zpráva

Research Report

2211

ÚTIA AV ČR, v.v.i

Praha

2008

Ing. Václav Šmídl, Ph.D. (ÚTIA - Oddělení adaptivních systémů)

distributed control, Bayesian decision-making, decentralized

Decentralized adaptive control is based on the use of many local controllers in parallel, each of them estimating its own local model and pursuing its local aims. If each controller designs its strategy using only its own model, the resulting control may be poor since consequences of actions of the neighbors are not taken into account. We seek a way how to improve algorithm of decision strategy design of a single local controller without significant increase in complexity of the local model or complexity of the design procedure. In this paper we study variants of distributed dynamic programming that could be evaluated locally. Specifically, we will investigate variants of the fully probabilistic control strategy design. Distributed and cen- tralized control strategies will be compared.