Adaptive Fixed-Time Output-Feedback Optimal Time-Varying Formation Control for Multiple Omnidirectional Robot Systems

被引:6
作者
Zhang, Jiaxin [1 ]
Fu, Yue [1 ]
Fu, Jun [1 ]
机构
[1] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
基金
中国国家自然科学基金;
关键词
Robots; Formation control; Output feedback; Wheels; Task analysis; Optimal control; Nonlinear systems; Fixed-time control; fuzzy state observers; multiple omnidirectional robot systems (MORSs); optimal time-varying formation (TVF); 2ND-ORDER MULTIAGENT SYSTEMS; CONSENSUS; TRACKING;
D O I
10.1109/TFUZZ.2023.3308573
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article presents an adaptive fuzzy fixed-time output feedback control approach for achieving an optimal time-varying formation (TVF) of multiple omnidirectional robot systems (MORSs) with uncertain external disturbances. Given that only output variables of the system are measurable, the method employs fuzzy state observers to reconstruct other unmeasured states. Novel performance index functions that incorporate exponential power terms are developed to achieve the optimization of a formation control system's performance. This function is utilized to design a fixed-time optimal scheme based on an identifier-actor-critic structure, which is a well-established control framework. Through rigorous analysis, it is proved that the proposed scheme guarantees fixed-time boundedness of all signals in the system and achieves formation control at a minimum cost. The comparative simulations and data analyses verify the effectiveness and superiority of the proposed control algorithm.
引用
收藏
页码:792 / 803
页数:12
相关论文
共 31 条
  • [1] Neural Network-Based Formation Control With Target Tracking for Second-Order Nonlinear Multiagent Systems
    Aryankia, Kiarash
    Selmic, Rastko R.
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2022, 58 (01) : 328 - 341
  • [2] Adaptive Fuzzy Practical Fixed-Time Tracking Control of Nonlinear Systems
    Chen, Ming
    Wang, Huanqing
    Liu, Xiaoping
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2021, 29 (03) : 664 - 673
  • [3] Taming Mismatches in Inter-agent Distances for the Formation-Motion Control of Second-Order Agents
    de Marina, Hector Garcia
    Jayawardhana, Bayu
    Cao, Ming
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2018, 63 (02) : 449 - 462
  • [4] Distributed Event-Triggered Control for Multi-Agent Systems
    Dimarogonas, Dimos V.
    Frazzoli, Emilio
    Johansson, Karl H.
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2012, 57 (05) : 1291 - 1297
  • [5] Time-Varying Formation Tracking for Second-Order Multi-Agent Systems Subjected to Switching Topologies With Application to Quadrotor Formation Flying
    Dong, Xiwang
    Zhou, Yan
    Ren, Zhang
    Zhong, Yisheng
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2017, 64 (06) : 5014 - 5024
  • [6] Time-varying formation control for general linear multi-agent systems with switching directed topologies
    Dong, Xiwang
    Hu, Guoqiang
    [J]. AUTOMATICA, 2016, 73 : 47 - 55
  • [7] Leader-Follower Formation Control of USVs With Prescribed Performance and Collision Avoidance
    He, Shude
    Wang, Min
    Dai, Shi-Lu
    Luo, Fei
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (01) : 572 - 581
  • [8] Adaptive Fuzzy Fast Finite-Time Formation Control for Second-Order MASs Based on Capability Boundaries of Agents
    Lan, Jie
    Liu, Yan-Jun
    Xu, Tongyu
    Tong, Shaocheng
    Liu, Lei
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 30 (09) : 3905 - 3917
  • [9] Time-Varying Optimal Formation Control for Second-Order Multiagent Systems Based on Neural Network Observer and Reinforcement Learning
    Lan, Jie
    Liu, Yan-Jun
    Yu, Dengxiu
    Wen, Guoxing
    Tong, Shaocheng
    Liu, Lei
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, 35 (03) : 3144 - 3155
  • [10] Robust consensus of uncertain linear multi-agent systems via dynamic output feedback
    Li, Xianwei
    Soh, Yeng Chai
    Xie, Lihua
    [J]. AUTOMATICA, 2018, 98 : 114 - 123