Particle Filter Design for Robust Nonlinear Control System of Uncertain Heat Exchange Process with Sensor Noise and Communication Time Delay

Abstract

In this paper, a particle filter design scheme for a robust nonlinear control system of uncertain heat exchange process against noise and communication time delay is presented. The particle filter employs a cluster of particles and associated weights to approximate the posterior distribution of states and is capable of handling nonlinear and non-Gaussian issues. However, when the realistic given noise is much larger than that of the one modeled by the particle filter, the estimated posterior distribution is no longer reliable. Considering that, the exponential weights take the place of the original absolute particle weights in this paper, which act as an adjustment to the particle filter weights for a better state estimation. This adjustment for the weight of the particle filter takes into account the practical significance and can ensure the stability, tracking performance, and continuous operation of the control process incorporated with the particle filter. The simulation verifies the feasibility and usefulness of the method.

Robustness Analysis for Sundry Disturbed Open Loop Dynamics Using Robust Right Coprime Factorization

“…The heat exchange process with a spiral heat exchanger system, which includes uncertainty [33], and undergoes robust right factorization and stabilization, denoted as (18).…”

“…Particle weights are calculated using (A8). Then, the exponential weights and original ones are normalized for the subsequent estimation as (A6) and (A7) [33].…”