Adaptive Control of Asynchronous Sequential Machines with State Feedback

The problem of controlling deterministic asynchronous sequential machines with unknown transitions is considered. The objective is to develop adaptive state feedback controllers that acquire data about unknown transitions and utilize these data to improve closed-loop performance. Presented are adaptation and control methodologies based on an algorithm that tests unknown transitions and records their outcomes without interfering with user experience.