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Adaptive control of stochastic manufacturing systems with hidden Markovian demands and small noise
Duncan, Tyrone E. Pasik-Duncan, Bozenna Zhang, Q.
Duncan, Tyrone E.
Pasik-Duncan, Bozenna
Zhang, Q.
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Abstract
The adaptive production planning of failure-prone manufacturing systems is considered in this paper, 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. In this paper, the authors 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 nearly optimal.
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©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Date
1999-02
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IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Keywords
Hidden Markov chain, Nearly optimal control, Parameter identification, Production planning
Citation
Duncan, TE; Pasik-Duncan, B; Zhang, Q. Adaptive control of stochastic manufacturing systems with hidden Markovian demands and small noise. IEEE TRANSACTIONS ON AUTOMATIC CONTROL. February 1999. 44(2) : 427-430