Hierarchical distributed model predictive control based on fuzzy negotiation

被引:14
作者
Masero, Eva [1 ]
Francisco, Mario [2 ]
Maestre, Jose M. [1 ]
Revollar, Silvana [2 ]
Vega, Pastora [3 ]
机构
[1] Univ Seville, Escuela Tecn Super Ingn, Dept Syst Engn & Automat, Av Camino Descubrimientos S-N, Seville 41092, Spain
[2] Univ Salamanca, Escuela Tecn Super Ingn Ind, Dept Comp & Automat, Av Fernando Ballesteros, Salamanca 37700, Spain
[3] Univ Salamanca, Fac Ciencias, Dept Comp & Automat, Plaza Merced S-N, Salamanca 37008, Spain
基金
欧洲研究理事会;
关键词
Model predictive control; Hierarchical distributed control; Pairwise negotiations; Fuzzy logic; Multi-agent systems; Stability; DESIGN; MPC; COMMUNICATION;
D O I
10.1016/j.eswa.2021.114836
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This work presents a hierarchical distributed model predictive control approach for multiple agents with cooperative negotiations based on fuzzy inference. Specifically, a fuzzy-based two-layer control architecture is proposed. In the lower control layer, there are pairwise negotiations between agents according to the couplings and the communication network. The resulting pairwise control sequences are sent to a coordinator in the upper control layer, which merges them to compute the final ones. Furthermore, conditions to guarantee feasibility and stability in the closed-loop system are provided. The proposed control algorithm has been tested on an eightcoupled tank plant via simulation.
引用
收藏
页数:13
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共 42 条
  • [21] A Distributed MPC scheme with Low Communication Requirements
    Maestre, J. M.
    Munoz de la Pena, D.
    Camacho, E. F.
    [J]. 2009 AMERICAN CONTROL CONFERENCE, VOLS 1-9, 2009, : 2797 - 2802
  • [22] Robust model predictive control for nonlinear discrete-time systems
    Magni, L
    De Nicolao, G
    Scattolini, R
    Allgöwer, F
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2003, 13 (3-4) : 229 - 246
  • [23] Prediction-driven coordination of distributed MPC controllers for linear unconstrained dynamic systems
    Marcos, Natalia I.
    Forbes, J. Fraser
    Guay, Martin
    [J]. INTERNATIONAL JOURNAL OF CONTROL, 2014, 87 (08) : 1496 - 1512
  • [24] A LOOP SHAPING DESIGN PROCEDURE USING H-INFINITY-SYNTHESIS
    MCFARLANE, D
    GLOVER, K
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1992, 37 (06) : 759 - 769
  • [25] Self-Triggered DMPC Design or Cooperative Multiagent Systems
    Mi, Xiaoxiao
    Zou, Yuanyuan
    Li, Shaoyuan
    Karimi, Hamid Reza
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2020, 67 (01) : 512 - 520
  • [26] Distributed Model Predictive Control AN OVERVIEW AND ROADMAP OF FUTURE RESEARCH OPPORTUNITIES
    Negenborn, R. R.
    Maestre, J. M.
    [J]. IEEE CONTROL SYSTEMS MAGAZINE, 2014, 34 (04): : 87 - 97
  • [27] Invariant approximations of the minimal robust. positively invariant set
    Rakovic, SV
    Kerrigan, EC
    Kouramas, KI
    Mayne, DQ
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2005, 50 (03) : 406 - 410
  • [28] Comparative study of proportional-integral, sliding mode, and fuzzy logic controllers for power converters
    Raviraj, VSC
    Sen, PC
    [J]. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 1997, 33 (02) : 518 - 524
  • [29] Data-Centric Hierarchical Distributed Model Predictive Control for Smart Grid Energy Management
    Saad, Ahmed
    Youssef, Tarek
    Elsayed, Ahmed T.
    Amin, Amr
    Abdalla, Omar Hanafy
    Mohammed, Osama
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (07) : 4086 - 4098
  • [30] Designing a fuzzy Q-learning multi-agent quality control system for a continuous chemical production line - A case study
    Sahebjamnia, Navid
    Tavakkoli-Moghaddam, Reza
    Ghorbani, Narges
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2016, 93 : 215 - 226