A framework for optimization of sensor activation using most permissive observers

This paper considers the problem of finding dynamic sensor activation policies that satisfy the property of K-diagnosability for discrete event systems modeled by finite state automata. We begin by choosing a suitable information state for the problem and defining a controller. We then define a structure called the most permissive observer, which provides all feasible solutions for the controller (i.e., for sensor activations). By formulating the problem as a state disambiguation problem, we prove a number of monotonicity properties about the information state. Finally, we show that this formulation allows us to efficiently compute the set of all satisfactory control decisions at all points in the system´s execution.