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Data-Driven Controller Design for Boolean Control Networks

Model identification of Boolean control networks requires not only a vast amount of data but also renders the problem of high computational complexity. The introduced data-driven design method of a stabilizing feedback controller reduces the requirements on the data set compared to the traditional two step procedure, first model identification then controller design. The idea is that for output stabilization it is not necessary to know all the internal dynamics. To widen the applicability, the method is extended to design a high order feedback controller. All the introduced algorithms are illustrated with examples.