Optimal control of Boolean control networks with average cost: A policy iteration approach

• Autores: Yuhu Wu, Xi-Ming Sun, Xudong Zhao, Tielong Shen
• Localización: Automatica: A journal of IFAC the International Federation of Automatic Control, ISSN 0005-1098, Nº. 100, 2019, págs. 378-387
• Idioma: inglés
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• Resumen

  • 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.