Nonlinear system identification and control using a real-coded genetic algorithm

被引:107
作者
Chang, Wei-Der [1 ]
机构
[1] Shu Te Univ, Dept Comp & Commun, Kaohsiung 824, Taiwan
关键词
nonlinear system identification; parameters estimation; PID controller; real-coded genetic algorithm; optimization problem;
D O I
10.1016/j.apm.2005.11.024
中图分类号
T [工业技术];
学科分类号
08 [工学];
摘要
A real-coded genetic algorithm (GA) applied to the system identification and control for a class of nonlinear systems is proposed in this paper. It is well known that GA is a globally optimal method motivated from natural evolutionary concepts. For solving a given optimization problem, there are two different kinds of GA operations: binary coding and real coding. In general, a real-coded GA is more suitable and convenient to deal with most practical engineering applications. In this paper, in the beginning we attempt to utilize a real-coded GA to identify the unknown system which its structure is assumed to be known previously. Next, according to the estimated system model an optimal off-line PID controller is optimally solved by also using the real-coded GA. Two simulated examples are finally given to demonstrate the effectiveness of the proposed method. (c) 2005 Elsevier Inc. All rights reserved.
引用
收藏
页码:541 / 550
页数:10
相关论文
共 19 条
[1]
[Anonymous], 1991, Handbook of genetic algorithms
[2]
[Anonymous], 1995, NEUROCONTROL ITS APP
[3]
New hybrid genetic operators for real coded genetic algorithm to compute optimal control of a class of hybrid systems [J].
Arumugam, MS ;
Rao, MVC ;
Palaniappan, R .
APPLIED SOFT COMPUTING, 2005, 6 (01) :38-52
[4]
Astrom K. J., 1995, ADAPTIVE CONTROL
[5]
A real-coded genetic algorithm for training recurrent neural networks [J].
Blanco, A ;
Delgado, M ;
Pegalajar, MC .
NEURAL NETWORKS, 2001, 14 (01) :93-105
[6]
A PD-like self-tuning fuzzy controller without steady-state error [J].
Chao, CT ;
Teng, CC .
FUZZY SETS AND SYSTEMS, 1997, 87 (02) :141-154
[7]
Design of truss-structures for minimum weight using genetic algorithms [J].
Deb, K ;
Gulati, S .
FINITE ELEMENTS IN ANALYSIS AND DESIGN, 2001, 37 (05) :447-465
[8]
Goldberg D.E, 1989, GENETIC ALGORITHMS S
[9]
Optimization of an impact drive mechanism based on real-coded genetic algorithm [J].
Ha, JL ;
Fung, RF ;
Han, CF .
SENSORS AND ACTUATORS A-PHYSICAL, 2005, 121 (02) :488-493
[10]
New methodology for analytical and optimal design of fuzzy PID controllers [J].
Hu, B ;
Mann, GKI ;
Gosine, RG .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1999, 7 (05) :521-539