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Policy Iteration Approach to Average Optimal Control Problems for Boolean Control Networks

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Indexed by:会议论文

Date of Publication:2017-01-01

Included Journals:SCIE、EI、CPCI-S、Scopus

Page Number:7990-7995

Key Words:Boolean control networks; Logical networks; Semi-tensor product; Optimal control; Policy iteration

Abstract:This paper investigates the average infinite horizon optimal control problem for Boolean control networks (BCNs). Based on the semi-tensor product of matrices and Jordan decomposition technique, an optimality equation for the average infinite horizon problem of BCNs is presented. By resorting to Laurent series expression, a policy iteration algorithm, which can find the optimal solution in finite iteration steps, is deduced. As applications, the output tracking problem for BCNs and the intervention problem of cAMP receptor protein are investigated.

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