Model predictive control of a highly nonlinear process based on piecewise linear Wiener models

被引：8
|
作者：
Shafiee, Ghobad [1 ]
Arefi, MohammadMehdi [1 ]
Jahed-Motlagh, MohammadReza [2 ]
Jalali, AliAkbar [1 ]
机构：
[1] Iran Univ Sci & Technol, Dept Elect Engn, Tehran, Iran
[2] Iran Univ Sci & Technol, Dept Comp Engn, Tehran, Iran
来源：
2006 1ST IEEE INTERNATIONAL CONFERENCE ON E-LEARNING IN INDUSTRIAL ELECTRONICS | 2006年
关键词：
D O I：
10.1109/ICELIE.2006.347195
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 (MTC) 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 MTC and also less steady-state error in tracking the set-points.
引用
收藏
页码：113 / +
页数：2
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