Tuning of PI-PD controller using extended non-minimal state space model predictive control for the stabilized gasoline vapor pressure in a stabilized tower

摘要

Nonlinearities, uncertainties and large time delay widely exist in the industrial processes, which pose great difficulty to traditional proportional-integral-derivative (PID) control. Proportional-integral-proportional-derivative (PI-PD) controller, which is a modified form of PID controller, can get a better performance than PID control. However, due to the fact that PI-PD controller has an extra parameter, the difficulty of parameter adjustment is a major problem. In this paper, a new PI-PD method optimized by the extended non-minimal state space model predictive control (ENMSSMPC) is proposed to get the optimal parameters of PI-PD controller for dealing with the process complexity. The proposed PI-PD controller combines the advantage of ENMSSMPC and the simple structure of the PID controller and is tested on the stabilized gasoline vapor pressure in a stabilized tower. Results show that it outperforms traditional controllers such as PID controller, PI-PD controller, traditional model predictive control based PID and PIPD controllers (TPFC-PID and TPFC-PIPD) and IMC based Robust PID controller (Robust IMC-PID). (C) 2015 Elsevier B.V. All rights reserved.