Nonlinear system identification using genetic algorithms with application to feedforward control design

被引：0
|
作者：
Luh, GC [1 ]
Rizzoni, G [1 ]
机构：
[1] Tatung Inst Technol, Dept Mech Engn, Taipei, Taiwan
来源：
PROCEEDINGS OF THE 1998 AMERICAN CONTROL CONFERENCE, VOLS 1-6 | 1998年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A GAMAS-based system identification scheme is developed to construct NARX model of nonlinear systems. Several simulated examples demonstrate that it can be applied to identify both nonlinear continuous-time systems and discrete-time systems with acceptable accuracy. Inverting the identified NARX model, a feedforward controller may be derived to track desired time varying signal of nonlinear systems. Sufficient conditions of the invertibility of NARX model are proposed to investigate the existence of the inverse model. Simulation results depict the effectiveness of the feedforward controller with the aid of simple feedback controller designed for regulation purpose.
引用
收藏
页码：2371 / 2375
页数：5
相关论文
共 50 条
  • [31] Volterra system identification using adaptive genetic algorithms
    Abbas, HM
    Bayoumi, MM
    APPLIED SOFT COMPUTING, 2004, 5 (01) : 75 - 86
  • [32] System Identification of Hydraulic System Using RLS Algorithm for Feedforward Position Control
    Lee, Kyeong Ha
    Baek, Seung Guk
    Choi, Jong Yoon
    Park, Jae Jun
    Choi, Hyouk Ryeol
    Moon, Hyungpil
    Koo, Ja Choon
    2015 12TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI), 2015, : 63 - 65
  • [33] Training feedforward neural networks using genetic algorithms
    1600, Morgan Kaufmann Publ Inc, San Mateo, CA, USA (01):
  • [34] Nonlinear predictive control of a drying process using genetic algorithms
    Yuzgec, Ugur
    Becerikli, Yasar
    Turker, Mustafa
    ISA TRANSACTIONS, 2006, 45 (04) : 589 - 602
  • [35] Model structure selection for nonlinear system identification using feedforward neural networks
    Petrovic, I
    Baotic, M
    Peric, N
    IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL I, 2000, : 53 - 57
  • [36] Automated identification of tomato maturation using multilayer feedforward neural network with genetic algorithms (GA)
    Zhang, C.
    Fang, J.
    Pan, W.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2001, 17 (03): : 153 - 156
  • [37] Automatic identification of tomato maturation by using multilayer feedforward neural network with genetic algorithms(GA)
    Zhang, C.L.
    Fang, J.L.
    Pan, W.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2001, 17 (03):
  • [38] Feedforward control of the lateral position of a moving web using system identification
    Shin, KH
    Kwon, SO
    Kim, SH
    Song, SH
    2003 IEEE INDUSTRY APPLICATIONS CONFERENCE, VOLS 1-3: CROSSROADS TO INNOVATIONS, 2003, : 345 - 351
  • [39] Feedforward control of the lateral position of a moving Web using system identification
    Shin, KH
    Kwon, SO
    Kim, SH
    Song, SH
    IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2004, 40 (06) : 1637 - 1643
  • [40] Integrated optimal design of vibration control system for smart beams using genetic algorithms
    Yang, YW
    Jin, ZL
    Soh, CK
    JOURNAL OF SOUND AND VIBRATION, 2005, 282 (3-5) : 1293 - 1307
12345