An Improved Method of Model-Free Adaptive Predictive Control: A Case of pH Neutralization in WWTP

被引:2
|
作者
Li, Jufeng [1 ]
Tang, Zhihe [1 ]
Luan, Hui [1 ]
Liu, Zhongyao [2 ]
Xu, Baochang [2 ]
Wang, Zhongjun [2 ]
He, Wei [1 ]
机构
[1] CNPC Res Inst Safety & Environm Technol, HSE Testing Ctr, Beijing 102206, Peoples R China
[2] China Univ Petr, Coll Informat Sci & Engn, Beijing 102249, Peoples R China
关键词
pH control; nonlinear; time-delay; model-free adaptive predictive control; robustness; PERFORMANCE; SYSTEMS; DESIGN; MPC;
D O I
10.3390/pr11051448
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
pH neutralization reaction process plays a crucial role in Waste Water Treatment Process (WWTP). Traditional PID Proportion Integral Differential, (or even advanced PID control) algorithms have poor performance on WWTP due to the strong non-linearity, large time lag, and large inertia characteristics of pH neutralization. Therefore, finding a superior control method to maintain the pH value of wastewater within the normal range will greatly help to improve the efficiency and effectiveness of wastewater treatment. The chemical reaction mechanism of pH neutralization reaction process is first analyzed, and a mechanistic model of pH neutralization reaction process is developed based on the reaction of ions during acid-alkali neutralization and the electric balance equation. Then, combining the characteristics of generalized predictive control and Model-Free Adaptive Control (MFAC), a Model-Free Adaptive Predictive Control (MFAPC) method based on compact format dynamic linearization is introduced. An Improved Model Free Adaptive PI Predictive Control algorithm (IMFAPC) with proportional (P) and integral (I) algorithms is proposed to further improve the control performance. IMFAPC is proposed on the basis of MFAPC, combining the advantages of generalized predictive control, introducing a PI module consisting of error and error sum, and predicting the PI module, making it possible to produce more accurate constraints on the control inputs, avoiding increasing errors, and improving the control effect of delayed systems at the same time. pH neutralization process simulation experimental results show that compared with the ordinary Model-Free Adaptive Control (MFAC) and MFAPC, the IMFAPC control algorithms has the best performance in terms of accuracy, overshoot, and the robustness.
引用
收藏
页数:19
相关论文
共 50 条
  • [41] Multi-unmanned surface vehicle model-free sliding mode predictive adaptive formation control and obstacle avoidance in complex marine environment via model-free extended state observer
    Luo, Qianda
    Wang, Hongbin
    Li, Ning
    Zheng, Wei
    OCEAN ENGINEERING, 2024, 293
  • [42] Model-free predictive control for a class of asymmetric nonlinear systems
    Su, Baili
    Tian, Ye
    Wang, Yunshuo
    ASIAN JOURNAL OF CONTROL, 2023, 25 (06) : 4291 - 4301
  • [43] Model Free Adaptive Predictive Control of Desulfurization Slurry pH Based on CPS Framework
    Liu J.
    Li X.
    Wang K.
    Wang F.
    Cui G.
    Journal of Beijing Institute of Technology (English Edition), 2020, 29 (04): : 544 - 555
  • [44] Distributed Model-Free Adaptive Predictive Control for MIMO Multi-Agent Systems With Deception Attack
    Pan, Zhenzhen
    Chi, Ronghu
    Hou, Zhongsheng
    IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, 2024, 10 : 32 - 47
  • [45] Model-Free Adaptive Predictive Quantitative Control for Nonlinear Systems subject to False Data Injection Attacks
    Liu, Genfeng
    Wang, Yangyang
    Hou, Zhongsheng
    2024 14TH ASIAN CONTROL CONFERENCE, ASCC 2024, 2024, : 503 - 508
  • [46] Model-Free Deadbeat Predictive Current Control for SPMSM Based on Adaptive Gain Extended State Observer
    Wu, Xuan
    Kang, Jinyu
    Yang, Meizhou
    Wu, Ting
    Huang, Shoudao
    IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2025, 11 (01): : 536 - 543
  • [47] Model-free control
    Fliess, Michel
    Join, Cedric
    INTERNATIONAL JOURNAL OF CONTROL, 2013, 86 (12) : 2228 - 2252
  • [48] An Overview of Model-Free Adaptive Control for the Wheeled Mobile Robot
    Zhang, Chen
    Cen, Chen
    Huang, Jiahui
    WORLD ELECTRIC VEHICLE JOURNAL, 2024, 15 (09):
  • [49] Model-Free Predictive Current Control of Synchronous Reluctance Motor Drives for Pump Applications
    De Martin, Ismaele Diego
    Pasqualotto, Dario
    Tinazzi, Fabio
    Zigliotto, Mauro
    MACHINES, 2021, 9 (10)
  • [50] Predictive control with adaptive model maintenance: Application to power plants
    Chan, K. H.
    Dozal-Mejorada, E. J.
    Cheng, X.
    Kephart, R.
    Ydstie, B. E.
    COMPUTERS & CHEMICAL ENGINEERING, 2014, 70 : 91 - 103