Recursive Sensor Allocation For A Class Of Distributed Parameter Systems (original) (raw)

This paper considers the problem of locating a sensor for the state estimation of a linear stochastic distributed parameter system of parabolic type, with observations taken at discrete times 1 1 ,12' .... Assuming that k measurements have been taken, the location of the measurement at time Ik+1 is selected, within a given set of admissible measurement points, in such a way as to minimize the spatial integral of the estimation error variance at time Ik+I' An algorithm is proposed, which incorporates the sclection of thc measurement point into a discrete-time Kalman filter that gives a finite-dimensional approximation of the state estimate. The characteristic features of the sequence of measurement points obtained by the algorithm are discussed on the basis of several numerical experiments. Finally, it is pointed out how the procedure can be applied to the solution of problems such as the allocation of a fixed sensor, the determination of the trajectory of a moving sensor, and the measurements scheduling among a predetermincd set of sensors.