State estimation of a nonlinear system using particle filter

Abstract

In this paper, Particle Filter algorithm has been employed for estimating the states namely concentration and temperature of a Continuous Stirred Tank Reactor (CSTR) and simulation results are presented. The propagation of particles through the nonlinear system model for the state estimation has been discussed. The states of the system are estimated by using the Particle Filter algorithm under the steady state as well as transient system conditions. A step change in the coolant flow rate has been introduced in order to provide a dynamic operating point.