Title :
Model Predictive Control of a Highly Nonlinear Process Based on Piecewise Linear Wiener Models
Author :
Shafiee, Ghobad ; Arefi, MohammadMehdi ; Jahed-Motlagh, MohammadReza ; Jalali, AliAkbar
Author_Institution :
Dept. of Electr. Eng., Iran Univ. of Sci. & Technol., Tehran
Abstract :
In this paper a nonlinear model predictive control (NMPC) based on a piecewise linear Wiener model is presented. The nonlinear gain of this particular Wiener model is approximated using the piecewise linear functions. This approach retains all the interested properties of the classical linear model predictive control (MPC) and keeps computations easy to solve due to the canonical structure of the nonlinear gain. The presented control scheme is applied to a pH neutralization process and simulation results are compared to linear model predictive control. Simulation results show that the nonlinear controller has better performance without any overshoot in comparison with linear MPC and also less steady-state error in tracking the set-points
Keywords :
nonlinear control systems; predictive control; stochastic processes; nonlinear gain; nonlinear model predictive control; pH neutralization process; piecewise linear Wiener models; Computational modeling; Error correction; Manufacturing processes; Nonlinear control systems; Open loop systems; Piecewise linear approximation; Piecewise linear techniques; Polymers; Predictive control; Predictive models;
Conference_Titel :
E-Learning in Industrial Electronics, 2006 1ST IEEE International Conference on
Conference_Location :
Hammamet
Print_ISBN :
1-4244-0324-3
Electronic_ISBN :
1-4244-0324-3
DOI :
10.1109/ICELIE.2006.347195
