Computational Issues In a Nonlinear Observer for Systems With Quantized Outputs

Abstract

In this paper we develop an observer for nonlinear systems with quantized outputs. The observer is a recursive algorithm based on the intersection of sets: each measurement defines a set in state space which, by recursive intersection, is used to refine knowledge of the state. We develop the necessary data structures and procedures to implement the algorithm numerically. Comparisons are drawn between the proposed observer, the Kalman filter, and the equations of nonlinear filtering. Estimates are given for the error due to the triangulation of the set of consistent states and the computational complexity of the numerical implementation of our observer. Finally, the algorithm is applied to two example systems.