Adaptive model-based control of non-linear plants using neural networks and fuzzy logic

被引：0
|
作者：
Melin, P [1 ]
Valerio, F [1 ]
Ramirez, M [1 ]
Sanchez, A [1 ]
机构：
[1] Tijuana Inst Technol, Dept Comp Sci, Chula Vista, CA 91909 USA
来源：
SOFT COMPUTING AND INDUSTRY: RECENT APPLICATIONS | 2002年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We describe in this paper adaptive model-based control of the inverted pendulum using a new hybrid approach combining neural networks and fuzzy logic. Intelligent control of complex plants is a difficult problem because the dynamics of these systems is highly non-linear. We describe an intelligent system for controlling the inverted pendulum to illustrate our new hybrid approach for adaptive control. We use the mathematical model of the inverted pendulum as s reference model in the control, and a set of fuzzy rules for representing the expert knowledge in controlling the non-linear dynamical system. We also consider a neuro-fuzzy approach to optimize the parameters of the fuzzy system for control.
引用
收藏
页码：123 / 132
页数：10
相关论文
共 50 条
  • [41] Runge-Kutta model-based adaptive predictive control mechanism for non-linear processes
    Iplikci, Serdar
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2013, 35 (02) : 166 - 180
  • [42] Non-linear adaptive inverse control based on fuzzy CMAC network
    Hou, Hai-Jun
    Lei, Yong
    Ye, Xiao-Yong
    Xitong Fangzhen Xuebao / Journal of System Simulation, 2008, 20 (08): : 2039 - 2043
  • [43] Feedforward control of a non-linear pneumatic muscle system using fuzzy logic
    Balasubramanian, K
    Rattan, KS
    PROCEEDINGS OF THE 12TH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1 AND 2, 2003, : 272 - 277
  • [44] Extended dynamic fuzzy logic system (DFLS) based indirect stable adaptive control of non-linear systems
    Murthy, OVR
    Bhatt, RKP
    Ahmad, N
    APPLIED SOFT COMPUTING, 2004, 4 (02) : 109 - 119
  • [45] Indirect adaptive fuzzy control of non-linear systems using fuzzy supervisory term
    Abid, Donia Ben Halima
    Chtourou, Mohamed
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2019, 59 (02) : 130 - 141
  • [46] State space neural networks in non-linear adaptive system identification and control
    Henriques, J
    Gil, P
    Dourado, A
    ADVANCED FUZZY-NEURAL CONTROL 2001, 2002, : 99 - 104
  • [47] Adaptive fuzzy control for uncertain non-linear systems
    Hamzaoui, A
    Zaytoon, J
    Elkari, A
    CONTROL APPLICATIONS OF OPTIMIZATION 2000, VOLS 1 AND 2, 2000, : 137 - 141
  • [48] Adaptive fuzzy control for a class of non-linear systems
    Zhao, Q. C.
    Ji, W.
    IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION, 2012, 29 (04) : 573 - 592
  • [49] Fault detection using non-linear model-based approach
    Valh, D
    Bratina, B
    Tovornik, B
    ISIE 2005: Proceedings of the IEEE International Symposium on Industrial Electronics 2005, Vols 1- 4, 2005, : 211 - 215
  • [50] Identification of Non-Linear Systems, Based on Neural Networks, with Applications at Fuzzy Systems
    Volosencu, Constantin
    RECENT ADVANCES IN AUTOMATION & INFORMATION: PROCEEDINGS OF THE 10TH WSEAS INTERNATIONAL CONFERENCE ON AUTOMATION & INFORMATION (ICAI'09), 2009, : 387 - +
12345