Model based multi-loop predictive control scheme for multivariable processes

被引:0
|
作者
Ramaveerapathiran, Arun [1 ]
Rathinam, Muniraj [2 ]
Natarajan, Karuppiah [3 ]
Athi, Muthiah [4 ]
Mounica, Patil [3 ]
机构
[1] Sri Sivasubramaniya Nadar Coll Engn, Dept Elect & Elect Engn, Chennai 603110, Tamilnadu, India
[2] PSR Engn Coll, Dept Elect & Elect Engn, Sivakasi 626140, Tamilnadu, India
[3] Vardhaman Coll Engn, Dept Elect & Elect Engn, Hyderabad 501218, Telangana, India
[4] PSR Engn Coll, Dept Mech Engn, Sivakasi 626140, Tamilnadu, India
关键词
Model based controller; Multi-loop control scheme; Internal model controller; DESIGN;
D O I
10.1007/s42452-025-06615-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Industry applications of multi loop controller approaches are common because of their robustness, minimal tuning parameter, and straightforward design. A model based multi-loop predictive control method is presented. The proposed method directly uses the process model without approximation and reduction. A sequential relay based auto tuning procedure is applied for the tuning of the controller parameters. The efficacy of the suggested multi-loop control strategy is illustrated through comparative analysis and simulation. Simulation results show that the proposed method gives better response in terms of Integral Absolute Error value compared to multi-loop PI controller tuned by other methods. The proposed predictive method has IAE value of 28.9 whereas Biggest Log Modulus Tuning method has 55.34 for the Wood and Berry distillation column process. Alike, the proposed predictive method has IAE value of 350.26 whereas BLT method has 360.01 for the Orgunnaike and Ray distillation column process. In general, the multi-loop predictive PI scheme improves the overall performance.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Detuning Iterative Continuous Cycling based Multi-loop PI control for multivariable processes
    Khandelwal, Shubham
    Detroja, Ketan P.
    2019 AUSTRALIAN & NEW ZEALAND CONTROL CONFERENCE (ANZCC), 2019, : 173 - 178
  • [2] Heuristic-based multi-scale control procedure of simultaneous multi-loop PID tuning for multivariable processes
    Nandong, Jobrun
    JOURNAL OF PROCESS CONTROL, 2015, 35 : 101 - 112
  • [3] Multi-loop adaptive internal model control based on a dynamic partial least squares model
    Zhao, Zhao
    Hu, Bin
    Liang, Jun
    JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE A, 2011, 12 (03): : 190 - 200
  • [4] A Stability-Guarantee Beamforming Scheme in Multi-Loop Wireless Control Systems
    Wang, Zining
    Lin, Min
    Jiang, Zhengmang
    Zhu, Wei-Ping
    Wang, Jiangzhou
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2024, 73 (10) : 15745 - 15750
  • [5] The speed control of PMLSM with discontinuous driving coils based on multi-loop DOB model
    Xiang, Biao
    Wen, Tao
    Wen, Tong
    ISA TRANSACTIONS, 2024, 146 : 366 - 379
  • [6] A comparative study of single-loop control and multi-loop control of gas turbine
    Wang, Li
    Zhang, Fan
    Xue, Yali
    IFAC PAPERSONLINE, 2022, 55 (09): : 525 - 530
  • [7] Multi-loop Internal Model Controller Design Based on a Dynamic PLS Framework
    Hu Bin
    Zheng Pingyou
    Liang Jun
    CHINESE JOURNAL OF CHEMICAL ENGINEERING, 2010, 18 (02) : 277 - 285
  • [8] Price-Based Adaptive Scheduling in Multi-Loop Control Systems With Resource Constraints
    Molin, Adam
    Hirche, Sandra
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2014, 59 (12) : 3282 - 3295
  • [9] Implement an efficient multi-loop control scheme using rapid estimating filters to compensate for a variety of voltage drops
    Mirzanejad, Hossein
    Sadeghi, Shahaboddin
    Salajegheh, Ehsan
    2021 IEEE 18TH INTERNATIONAL CONFERENCE ON SMART COMMUNITIES: IMPROVING QUALITY OF LIFE USING ICT, IOT AND AI (IEEE HONET 2021), 2021, : 77 - 82
  • [10] MIMO modeling and multi-loop control based on neural network for municipal solid waste incineration
    Ding, Haixu
    Tang, Jian
    Qiao, Junfei
    CONTROL ENGINEERING PRACTICE, 2022, 127