Enhancing the performance of the particle filtering optimization algorithm for the tuning of PID controllers

Abstract:

PID controllers are widely used in the control of industrial processes. Proper performance of the PID compensator is achieved when optimal parameters values of the PID are identified. Particle based Optimization algorithms are commonly used in solving parameter optimization problems. In this work, a particle based optimization algorithm is proposed. The methodology improves the performance of the Particle Filtering Optimization algorithm by considering the EnKF as part of the PFO algorithm. Two structures are considered in this study: PFO with the EnKF and SIR filter and PFO with the EnKF. Simulation results show that the inclusion of the EnKF improves the performance of the PFO algorithm even with a small set of particles and the computational time demand of the combined methodology is slightly increased.

Año de publicación:

2017

Keywords:

• PID CONTROL
• Particle Swarm Optimization
• ensemble Kalman filter
• Particle Filtering Optimization

Fuente:

scopus