Fast Finite-Time Tracking Consensus With Applications on Multiple Servo Motors

被引:19
作者
Zheng, Shiqi [1 ,2 ]
Shi, Peng [3 ]
Xie, Yuanlong [4 ]
Wang, Shuting [4 ]
机构
[1] China Univ Geosci, Sch Automat, Wuhan 430074, Peoples R China
[2] Hubei key Lab Adv Control & Intelligent Automat Co, Wuhan, Peoples R China
[3] Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, Australia
[4] Huazhong Univ Sci & Technol, Sch Mech Sci & Engn, Wuhan 430074, Peoples R China
关键词
Adaptive control; adding a power integrator; backstepping; finite-time control; state constraints; ACTIVE SUSPENSION SYSTEMS; ADAPTIVE ROBUST-CONTROL;
D O I
10.1109/TIE.2022.3174244
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 article focuses on the fast finite-time tracking consensus for uncertain nonlinear multiagent systems. By gracefully combining the hierarchical decomposition, adding a barrier power integrator and disturbance compensation techniques, a new adaptive fast finite-time controller is proposed. Compared with the existing works, the proposed method has several distinguishing features: 1) It can achieve fast finite-time convergence with full state constraints; 2) it can deal with some fully unknown nonlinearities and state-dependent disturbance. Moreover, the nonlinearities can be related with the states of all the followers; 3) the input of the leader is not required to be zero, meaning a broad class of references signals can be generated; and 4) the controller is computationally simply and ready to be implemented. No fuzzy logic/neural networks are needed. Applications of the proposed method on multiple servo motors are also studied.
引用
收藏
页码:2993 / 3002
页数:10
相关论文
共 33 条
  • [1] Finite-Time Fuzzy Adaptive Consensus for Heterogeneous Nonlinear Multi-Agent Systems
    Chen, Duxin
    Liu, Xiaolu
    Yu, Wenwu
    [J]. IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2020, 7 (04): : 3057 - 3066
  • [2] Distributed Resilient Secondary Control for DC Microgrids Against Heterogeneous Communication Delays and DoS Attacks
    Deng, Chao
    Guo, Fanghong
    Wen, Changyun
    Yue, Dong
    Wang, Yu
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2022, 69 (11) : 11560 - 11568
  • [3] Design and Implementation of Bounded Finite-Time Control Algorithm for Speed Regulation of Permanent Magnet Synchronous Motor
    Du, Haibo
    Wen, Guanghui
    Cheng, Yingying
    Lu, Jinhu
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 68 (03) : 2417 - 2426
  • [4] Distributed fixed-time consensus for nonlinear heterogeneous multi-agent systems
    Du, Haibo
    Wen, Guanghui
    Wu, Di
    Cheng, Yingying
    Lu, Jinhu
    [J]. AUTOMATICA, 2020, 113
  • [5] Disturbance Observer-Based Finite-Time Control for Three-Phase AC-DC Converter
    Fu, Cheng
    Zhang, Chenghui
    Zhang, Guanguan
    Song, Jinqiu
    Zhang, Chen
    Duan, Bin
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2022, 69 (06) : 5637 - 5647
  • [6] Adaptive finite-time consensus control of a group of uncertain nonlinear mechanical systems
    Huang, Jiangshuai
    Wen, Changyun
    Wang, Wei
    Song, Yong-Duan
    [J]. AUTOMATICA, 2015, 51 : 292 - 301
  • [7] Adaptive Fuzzy Behavioral Control of Second-Order Autonomous Agents With Prioritized Missions: Theory and Experiments
    Huang, Jie
    Zhou, Ning
    Cao, Ming
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 66 (12) : 9612 - 9622
  • [8] Decoupled Fractional Supertwisting Stabilization of Interconnected Mobile Robot Under Harsh Terrain Conditions
    Jiang, Liquan
    Wang, Shuting
    Xie, Yuanlong
    Xie, Shengquan
    Zheng, Shiqi
    Meng, Jie
    Ding, Han
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2022, 69 (08) : 8178 - 8189
  • [9] Continuous Finite-Time Output Regulation for Disturbed Systems Under Mismatching Condition
    Li, Shihua
    Sun, Haibin
    Yang, Jun
    Yu, Xinghuo
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2015, 60 (01) : 277 - 282
  • [10] Observer-Based Neuro-Adaptive Optimized Control of Strict-Feedback Nonlinear Systems With State Constraints
    Li, Yongming
    Liu, Yanjun
    Tong, Shaocheng
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 33 (07) : 3131 - 3145