OPTIMAL SENSOR SCHEDULING IN CONTINUOUS TIME

In this paper, we consider an optimal sensor scheduling problem in continuous time. This problem aims to find an optimal sensor schedule such that the corresponding estimation error is minimized. It is formulated as a deterministic optimal control problem involving both discrete and continuous valued controls. A computational method is developed for solving this deterministic optimal control problem based on a branch and bound method in conjunction with a gradient-based method. The branch and bound method is used to determine the optimal switching sequence of sensors, where a sequence of lower bound dynamic systems is introduced so as to provide effective lower bounds for the construction of the branching rules. For a given switching sequence, determining the respective optimal switching time is a continuous-valued optimal control problem and can be solved by gradient-based method with appropriate gradient formulae. This computational method is very efficient, as demonstrated by the numerical examples.