Control of a MIMO Coupled Plant Using a Neuro-Fuzzy Adaptive System Based on Boolean Relations

被引:6
作者
Espitia, Helbert [1 ]
Machon, Ivan [2 ]
Lopez, Hilario [2 ]
机构
[1] Univ Distrital Francisco Jose de Caldas, Fac Ingn, Bogota 11021110231, Colombia
[2] Univ Oviedo, Dept Ingn Elect Elect Computadores & Sistemas, Campus Viesques, Gijon 33203, Spain
关键词
Adaptive control; Adaptation models; MIMO communication; Control systems; Neural networks; Uncertainty; Fuzzy logic; Adaptive; control; hydraulic; MIMO; neuro-fuzzy; SLIDING MODE CONTROL; INFERENCE SYSTEM; DESIGN; MANAGEMENT;
D O I
10.1109/ACCESS.2021.3073067
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This document describes the implementation of a neuro-fuzzy adaptive system MIMO (Multiple Input Multiple Output), using two neuro-fuzzy MIMO systems: one for control and the other for identifying the plant. Under this approach, the controller is optimized, employing the model obtained during the identification of the plant that utilizes data generated from the controller's operation. In this way, the plant identification and the controller optimization is performed iteratively. The application case consists of controlling a MIMO non-linear hydraulic system fed by a pump and a three-way valve. In order to observe the controller performance various experimental configurations are considered.
引用
收藏
页码:59987 / 60009
页数:23
相关论文
共 62 条
  • [1] Spacecraft attitude control via a combined state-dependent Riccati equation and adaptive neuro-fuzzy approach
    Abdelrahman, Mohammad
    Park, Sang-Young
    [J]. AEROSPACE SCIENCE AND TECHNOLOGY, 2013, 26 (01) : 16 - 28
  • [2] An Adaptive Power Oscillation Damping Controller for a Hybrid AC/DC Microgrid
    Ahmed, Moudud
    Vahidnia, Arash
    Datta, Manoj
    Meegahapola, Lasantha
    [J]. IEEE ACCESS, 2020, 8 (08): : 69482 - 69495
  • [3] New hybrid adaptive neuro-fuzzy algorithms for manipulator control with uncertainties - Comparative study
    Alavandar, Srinivasan
    Nigam, M. J.
    [J]. ISA TRANSACTIONS, 2009, 48 (04) : 497 - 502
  • [4] Alshejari A., 2018, THESIS U WESTMINSTER
  • [5] [Anonymous], 2015, GLOBAL OPTIMIZATION
  • [6] Adaptive neuro-fuzzy control of an induction motor
    Areed, Fayez G.
    Haikal, Amira Y.
    Mohammed, Reham H.
    [J]. AIN SHAMS ENGINEERING JOURNAL, 2010, 1 (01) : 71 - 78
  • [7] Atia Doaa M., 2017, Journal of Electrical Systems and Information Technology, V4, P34, DOI 10.1016/j.jesit.2016.10.014
  • [8] Adaptive optimal multi-critic based neuro-fuzzy control of MIMO human musculoskeletal arm model
    Balaghi, M. Hadi E.
    Vatankhah, Ramin
    Broushaki, Mehrdad
    Alasty, Aria
    [J]. NEUROCOMPUTING, 2016, 173 : 1529 - 1537
  • [9] Balas V. E., 2020, ADAPTIVE INTELLIGENT, V161
  • [10] Beˇlohlavek R., 2017, Fuzzy Logic and Mathematics: A Historical Perspective