Driving a Discrete Event System to a Known State via Minimal Length Adaptive Control Sequences
Martha Christou, Christoforos N. Hadjicostis · IFAC-PapersOnLine · 2024
This paper studies a class of problems in which we are given the model of a system, with an unknown (or partially known) initial state, and the goal is to apply a carefully chosen sequence of inputs so that, based on the observations (outputs) that are generated, one can determine exactly the current state of the system. The sequence of control inputs is adaptive in the sense that each input is chosen based on the sequence of outputs observed so far and the sequence of inputs previously applied. The main solution for this type of problems involves current-state estimation along with a game structure that tracks the interleaving of control actions and system responses. The ability to determine exactly the current state of the system can be key for a variety of tasks, such as taking special actions (e.g., resetting the system) or supervisory control strategies that aim at achieving various objectives (e.g., avoiding deadlocks).