Special Appointed Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Paper Publications
Optimal control of Boolean control networks with average cost: A policy iteration approach
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Indexed by:Journal Article
Date of Publication:2019-02-01
Journal:AUTOMATICA
Included Journals:Scopus、SCIE
Volume:100
Page Number:378-387
ISSN:0005-1098
Key Words:Boolean control networks; Semi-tensor product (STP); Average optimal control; Infinite horizon optimal control; Policy iteration
Abstract:This paper deals with the infinite horizon optimal control problem for deterministic Boolean control networks (BCNs) with average cost. Based on the semi-tensor product of matrices and Jordan decomposition technique, a nested optimality equation for the average infinite horizon problem of BCNs is presented. By resorting to Laurent series expression, a novel policy iteration algorithm, which can find the optimal state feedback controller in finite iteration steps, is proposed. Finally, as a practical application, the optimal intervention problem of Ara operon in E. coil is addressed. (C) 2018 Elsevier Ltd. All rights reserved.