Adaptive control of stochastic manufacturing systems with hidden Markovian demands and small noise

Author

Duncan, T.E. ; Pasik-Duncan, B. ; Zhang, Q.

Author_Institution

Dept. of Math., Kansas Univ., Lawrence, KS, USA

Volume

4

fYear

1997

fDate

10-12 Dec 1997

Firstpage

4058

Abstract

The adaptive production planning of failure-prone manufacturing systems is considered. In real manufacturing systems, the product demand is usually not known a priori. One of the major tasks in production scheduling is to estimate and predict the demand. We consider the demand to be either the sum of an unknown rate and a small white noise or the sum of a hidden Markov chain and a small white noise. An algorithm is given to define a family of estimates for the unknown demand processes. Based on this family of estimates, adaptive controls are constructed, which are shown to be asymptotically optimal

Keywords

Markov processes; adaptive control; flexible manufacturing systems; production control; stochastic systems; white noise; adaptive control; adaptive production planning; failure-prone manufacturing systems; hidden Markovian demands; production scheduling; small white noise; stochastic manufacturing systems; unknown demand processes; Adaptive control; Hidden Markov models; Manufacturing systems; Mathematics; Parameter estimation; Production planning; Stochastic processes; Stochastic resonance; Stochastic systems; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1997., Proceedings of the 36th IEEE Conference on

Conference_Location

San Diego, CA

ISSN

0191-2216

Print_ISBN

0-7803-4187-2

Type

conf

DOI

10.1109/CDC.1997.652502

Filename

652502