Adaptive decentralized PID controllers design using JITL modeling methodology

被引:17
作者
Yang, Xin [1 ]
Jia, Li [2 ]
Chiu, Min-Sen [1 ]
机构
[1] Natl Univ Singapore, Dept Chem & Biomol Engn, Singapore 117576, Singapore
[2] Shanghai Univ, Coll Mechatron Engn & Automat, Dept Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China
基金
中国国家自然科学基金; 高等学校博士学科点专项科研基金;
关键词
Decentralized PID controller; Lyapunov method; Multivariable systems; Just-in-Time Learning; NONLINEAR PROCESS-CONTROL; LYAPUNOV APPROACH; NEURAL-NETWORKS; SYSTEMS; REACTOR; IDENTIFICATION; PLANT;
D O I
10.1016/j.jprocont.2012.05.018
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, an adaptive decentralized PID design is developed for multivariable systems. In the proposed design, the controller parameters are adjusted by an updating algorithm derived based on the Lyapunov method such that the predicted tracking error converges asymptotically. Toward this end, the Just-in-Time Learning method is incorporated into the proposed design to provide the information required for the updating algorithm. Simulation results illustrate that the proposed design achieves better control performance than its corresponding benchmark designs reported in the literature. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1531 / 1542
页数:12
相关论文
共 50 条
  • [21] Genetic tuning of PID controllers using a neural network model: A seesaw example
    Wu, CJ
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 1999, 25 (01) : 43 - 59
  • [22] Genetic Tuning of PID Controllers Using a Neural Network Model: A Seesaw Example
    Chia-Ju Wu
    Journal of Intelligent and Robotic Systems, 1999, 25 : 43 - 59
  • [23] Decentralized PID controller design for TITO processes with experimental validation
    Hajare V.D.
    Patre B.M.
    Khandekar A.A.
    Malwatkar G.M.
    International Journal of Dynamics and Control, 2017, 5 (3) : 583 - 595
  • [24] Adaptive Output Feedback Design Using Asymptotic Properties of LQG/LTR Controllers
    Lavretsky, Eugene
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2012, 57 (06) : 1587 - 1591
  • [25] Neural Adaptive PID Control of a Quadrotor using EFK
    Rosales, C.
    Tosetti, S.
    Soria, C.
    Rossomando, F.
    IEEE LATIN AMERICA TRANSACTIONS, 2018, 16 (11) : 2722 - 2730
  • [26] ADAPTIVE DIRECT DATA DRIVEN DESIGN FOR TWO DEGREES OF FREEDOM CONTROLLERS
    Dong, Liushuan
    Wang, Jianhong
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2022, 18 (03): : 783 - 800
  • [27] An islanded hybrid microgrid design with decentralized DC and AC subgrid controllers
    Kabalci, Ersan
    ENERGY, 2018, 153 : 185 - 199
  • [28] Design of PID controllers using Filippov's method for stable operation of DC-DC converters
    Hayes, Brendan
    Condon, Marissa
    Giaouris, Damian
    INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 2016, 44 (07) : 1437 - 1454
  • [30] Performance of robust PID and Q-design controllers for propofol anesthesia
    van Heusden, K.
    Ansermino, J. M.
    Dumont, G. A.
    IFAC PAPERSONLINE, 2018, 51 (04): : 78 - 83