2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于混合双端事件触发机制的协同控制策略研究

李冬妮 孙佳月 闫宇晴 张化光

李冬妮, 孙佳月, 闫宇晴, 张化光. 基于混合双端事件触发机制的协同控制策略研究. 自动化学报, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c220741
引用本文: 李冬妮, 孙佳月, 闫宇晴, 张化光. 基于混合双端事件触发机制的协同控制策略研究. 自动化学报, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c220741
Li Dong-Ni, Sun Jia-Yue, Yan Yu-Qing, Zhang Hua-Guang. Cooperative control strategy research based on hybrid dual-terminal event-triggered mechanism. Acta Automatica Sinica, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c220741
Citation: Li Dong-Ni, Sun Jia-Yue, Yan Yu-Qing, Zhang Hua-Guang. Cooperative control strategy research based on hybrid dual-terminal event-triggered mechanism. Acta Automatica Sinica, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c220741

基于混合双端事件触发机制的协同控制策略研究

doi: 10.16383/j.aas.c220741 cstr: 32138.14.j.aas.c220741
基金项目: 中组部万人领军青年拔尖人才支持计划 (QNBJ-2023-12), 国家自然科学基金 (62203097), 中央高校基本科研业务专项资金 (N2404018) 资助
详细信息
    作者简介:

    李冬妮:东北大学信息科学与工程学院博士研究生. 2024年获得渤海大学硕士学位. 主要研究方向为自适应控制, 神经网络控制, 多智能体系统的分布式控制及其应用. E-mail: lidongni1999@163.com

    孙佳月:东北大学信息科学与工程学院教授. 主要研究方向为复杂工业过程优化, 智能自适应学习, 多智能体系统分布式控制及其应用. 本文通信作者. E-mail: jyuesun@163.com

    闫宇晴:东北大学信息科学与工程学院博士研究生. 2018年获得辽宁师范大学学士学位. 主要研究方向为分数阶系统. E-mail: yanyuqing815@163.com

    张化光:东北大学信息科学与工程学院教授. 主要研究方向为模糊控制, 随机系统控制, 基于神经网络控制, 非线性控制及其应用. E-mail: hgzhang@ieee.org

Cooperative Control Strategy Research Based on Hybrid Dual-terminal Event-triggered Mechanism

Funds: Supported by National High-Level Talents Special Support Program (Youth Talent of Technological Innovation of Ten-Thousands Talents Program) (QNBJ-2023-12), National Natural Science Foundation of China (62203097), and the Fundamental Research Funds for the Central Universities (N2404018)
More Information
    Author Bio:

    LI Dong-Ni Ph.D. candidate at the College of Information Science and Engineering, Northeastern University. She received her master degree from Bohai University in 2024. Her research interest covers adaptive control, neural-networks control, distributed control of multiagent systems, and its applications

    SUN Jia-Yue Professor at the College of Information Science and Engineering, Northeastern University. Her research interest covers optimization of complex industrial processes, intelligent adaptive learning, distributed control of multi-agent systems and its applications. Corresponding author of this paper

    YAN Yu-Qing Ph.D. candidate at the College of Information Science and Engineering, Northeastern University. She received her bachelor degree from Liaoning Normal University in 2018. Her main research interest is fractional-order system

    ZHANG Hua-Guang Professor at the College of Information Science and Engineering, Northeastern University. His research interest covers fuzzy control, stochastic-system control, neural-network-based control, nonlinear control, and their applications

  • 摘要: 针对非线性多智能体系统, 提出基于混合双端事件触发机制的模糊跟踪控制策略. 首先, 相比于现存状态事件触发机制, 构建了一种灵活可调的阈值设计方法以满足系统实时性需求; 其次, 改进的状态触发机制将状态估计值作为触发信号, 可有效降低现存机制的保守性并提高阈值设计的灵活性; 随后, 针对控制器-执行器环节和传感器-控制器环节, 设计了混合双端事件触发机制来同时缓解双信道的通讯负担. 此外, 为了解决未知不可测状态的问题, 构造了一种仅基于相对输出信息的状态观测器. 最后, 在闭环系统内, 所有信号都是半全局一致最终稳定的, 并用一个实际的仿真例子证明了提出控制策略的有效性.
  • 图  1  通信拓扑图

    Fig.  1  The communication graphs

    图  2  四个跟随者和一个领导者的输出轨迹

    Fig.  2  The trajectories of the four followers and one leader

    图  3  跟踪误差的轨迹

    Fig.  3  The trajectories of tracking errors

    图  4  控制器的输入轨迹

    Fig.  4  The input trajectories of the controllers

    图  5  自适应律参数$\hat{\eta}_{h,\;1}$的轨迹

    Fig.  5  The trajectories of the adaptive laws $\hat{\eta}_{h,\;1}$

    图  6  自适应律参数$\hat{\eta}_{h,\;2}$的轨迹

    Fig.  6  The trajectories of the adaptive laws $\hat{\eta}_{h,\;2}$

    图  7  观测误差的变化情况

    Fig.  7  The observation errors $\Delta_{h,\;2}$

    图  8  四个智能体的事件触发间隔时间

    Fig.  8  The interevent times of four agents

  • [1] Guo X G, Zhang D Y, Wang J L, Park J H, Guo L. Observer-based event-triggered composite anti-disturbance control for multi-agent systems under multiple disturbances and stochastic FDIAs. IEEE Transactions on Automation Science and Engineering, 2023, 20(1): 528−540
    [2] Ren H R, Ma H, Li H Y, Wang Z Y. Adaptive fixed-time control of nonlinear MASs with actuator faults. IEEE/CAA Journal of Automatica Sinica, 2023, 10(5): 1252−1262
    [3] Cao L, Pan Y N, Liang H J, Huang T W. Observer-based dynamic event-triggered control for multiagent systems with time-varying delay. IEEE Transactions on Cybernetics, 2023, 53(5): 3376−3387 doi: 10.1109/TCYB.2022.3226873
    [4] Lin G H, Li H Y, Ma H, Zhou Q. Distributed containment control for human-in-the-loop MASs with unknown time-varying parameters. IEEE Transactions on Circuits and Systems I: Regular Papers, 2022, 69(12): 5300−5311
    [5] Liang H J, Chang Z Y, Ahn C K. Hybrid event-triggered intermittent control for nonlinear multi-agent systems. IEEE Transactions on Network Science and Engineering, 2023, 10(4): 1975−1984 doi: 10.1109/TNSE.2023.3237256
    [6] Zheng C B, Pang Z H, Wang J X, Sun J, Liu G P, Han Q L. Null-space-based time-varying formation control of uncertain nonlinear second-order multi-agent systems with collision avoidance. IEEE Transactions on Industrial Electronics, 2023, 70(10): 10476−10485 doi: 10.1109/TIE.2022.3217585
    [7] Wei C S, Luo J J, Dai H H, Duan G R. Learning-based adaptive attitude control of spacecraft formation with guaranteed prescribed performance. IEEE Transactions on Cybernetics, 2019, 49(11): 4004−4016 doi: 10.1109/TCYB.2018.2857400
    [8] Zuo Z Y, Liu C J, Han Q L, Song J W. Unmanned aerial vehicles: Control methods and future challenges. IEEE/CAA Journal of Automatica Sinica, 2022, 9(4): 601−614 doi: 10.1109/JAS.2022.105410
    [9] Heshmati-Alamdari S, Nikou A, Dimarogonas D V. Robust trajectory tracking control for underactuated autonomous underwater vehicles in uncertain environments. IEEE Transactions on Automation Science and Engineering, 2021, 18(3): 1288−1301 doi: 10.1109/TASE.2020.3001183
    [10] 杨涛, 柴天佑. 分布式协同优化的研究现状与展望. 中国科学: 技术科学, 2020, 50(11): 1414−1425 doi: 10.1360/SST-2020-0040

    Yang Tao, Chai Tian-You. Research status and prospects of distributed collaborative optimization. SCIENTIA SINICA Technologica, 2020, 50(11): 1414−1425 doi: 10.1360/SST-2020-0040
    [11] Liang H J, Chen L, Pan Y N, Lam H K. Fuzzy-based robust precision consensus tracking for uncertain networked systems with cooperative-antagonistic interactions. IEEE Transactions on Fuzzy Systems, 2023, 31(4): 1362−1376 doi: 10.1109/TFUZZ.2022.3200730
    [12] Liu G P. Tracking control of multi-agent systems using a networked predictive PID tracking scheme. IEEE/CAA Journal of Automatica Sinica, 2023, 10(1): 216−225 doi: 10.1109/JAS.2023.123030
    [13] Liu Z J, Lu Z Q, Zhao Z J, Efe M Ö, Hong K S. Single parameter adaptive neural network control for multi-agent deployment with prescribed tracking performance. Automatica, 2023, 156: 111207 doi: 10.1016/j.automatica.2023.111207
    [14] Ren H R, Cheng Z J, Qin J H, Lu R Q. Deception attacks on event-triggered distributed consensus estimation for nonlinear systems. Automatica, 2023, 154: 111100 doi: 10.1016/j.automatica.2023.111100
    [15] 杨涛, 徐磊, 易新蕾, 张圣军, 陈蕊娟, 李渝哲. 基于事件触发的分布式优化算法. 自动化学报, 2022, 48(1): 133−143

    Yang Tao, Xu Lei, Yi Xin-Lei, Zhang Sheng-Jun, Chen Rui-Juan, Li Yu-Zhe. Event-triggered distributed optimization algorithms. Acta Automatica Sinica, 2022, 48(1): 133−143
    [16] Pan Y N, Wu Y M, Lam H K. Security-based fuzzy control for nonlinear networked control systems with DoS attacks via a resilient event-triggered scheme. IEEE Transactions on Fuzzy Systems, 2022, 30(10): 4359−4368 doi: 10.1109/TFUZZ.2022.3148875
    [17] Zong G D, Ren H L. Guaranteed cost finite-time control for semi-Markov jump systems with event-triggered scheme and quantization input. International Journal of Robust and Nonlinear Control, 2019, 29(15): 5251−5273 doi: 10.1002/rnc.4672
    [18] Zhang M, Dong S L, Shi P, Chen G R, Guan X H. Distributed observer-based event-triggered load frequency control of multiarea power systems under cyber attacks. IEEE Transactions on Automation Science and Engineering, 2023, 20(4): 2435−2444
    [19] Zhang Y H, Sun J, Liang H J, Li H Y. Event-triggered adaptive tracking control for multiagent systems with unknown disturbances. IEEE Transactions on Cybernetics, 2020, 50(3): 890−901 doi: 10.1109/TCYB.2018.2869084
    [20] Chen Z Y, Niu B, Zhang L, Zhao J F, Ahmad A M, Alassafi M O. Command filtering-based adaptive neural network control for uncertain switched nonlinear systems using event-triggered communication. International Journal of Robust and Nonlinear Control, 2022, 32(11): 6507−6522 doi: 10.1002/rnc.6154
    [21] Li Y X, Yang G H, Tong S C. Fuzzy adaptive distributed event-triggered consensus control of uncertain nonlinear multiagent systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 49(9): 1777−1786 doi: 10.1109/TSMC.2018.2812216
    [22] Li Y M, Min X, Tong S C. Observer-based fuzzy adaptive inverse optimal output feedback control for uncertain nonlinear systems. IEEE Transactions on Fuzzy Systems, 2021, 29(6): 1484−1495
    [23] Tong S C, Sun K K, Sui S. Observer-based adaptive fuzzy decentralized optimal control design for strict-feedback nonlinear large-scale systems. IEEE Transactions on Fuzzy Systems, 2018, 26(2): 569−584 doi: 10.1109/TFUZZ.2017.2686373
    [24] Li Y M, Min X, Tong S C. Adaptive fuzzy inverse optimal control for uncertain strict-feedback nonlinear systems. IEEE Transactions on Fuzzy Systems, 2020, 28(10): 2363−2374 doi: 10.1109/TFUZZ.2019.2935693
    [25] Hou M Z, Shi W R, Fang L Y, Duan G R. Adaptive dynamic surface control of high-order strict feedback nonlinear systems with parameter estimations. Science China Information Sciences, 2023, 66(5): 159203
    [26] Ren H R, Ma H, Li H Y, Lu R H. A disturbance observer based intelligent control for nonstrict-feedback nonlinear systems. Science China Technological Sciences, 2023, 66: 456−467 doi: 10.1007/s11431-022-2126-7
    [27] Sun J Y, Zhang H G, Wang Y C, Sun S X. Fault-tolerant control for stochastic switched IT2 fuzzy uncertain time-delayed nonlinear systems. IEEE Transactions on Cybernetics, 2022, 52(2): 1335−1346 doi: 10.1109/TCYB.2020.2997348
    [28] Liu Z C, Huang J S, Wen C Y, Su X J. Distributed control of nonlinear systems with unknown time-varying control coefficients: A novel Nussbaum function approach. IEEE Transactions on Automatic Control, 2023, 68(7): 4191−4203
    [29] Liu G D, Sun N, Yang T, Fang Y C. Reinforcement learning-based prescribed performance motion control of pneumatic muscle actuated robotic arms with measurement noises. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(3): 1801−1812 doi: 10.1109/TSMC.2022.3207575
    [30] Liang H J, Zhang Y H, Huang T W, Ma H. Prescribed performance cooperative control for multiagent systems with input quantization. IEEE Transactions on Cybernetics, 2020, 50(5): 1810−1819 doi: 10.1109/TCYB.2019.2893645
    [31] Yu T, Ma L, Zhang H W. Prescribed performance for bipartite tracking control of nonlinear multiagent systems with hysteresis input uncertainties. IEEE Transactions on Cybernetics, 2019, 49(4): 1327−1338 doi: 10.1109/TCYB.2018.2800297
    [32] Zhang H W, Lewis F L, Qu Z H. Lyapunov, adaptive, and optimal design techniques for cooperative systems on directed communication graphs. IEEE Transactions on Industrial Electronics, 2012, 59(7): 3026−3041
    [33] Zhang H W, Lewis F L. Adaptive cooperative tracking control of higher-order nonlinear systems with unknown dynamics. Automatica, 2012, 48(7): 1432−1439 doi: 10.1016/j.automatica.2012.05.008
    [34] Zhang L L, Che W W, Deng C, Wu Z G. Prescribed performance control for multiagent systems via fuzzy adaptive event-triggered strategy. IEEE Transactions on Fuzzy Systems, 2022, 30(12): 5078−5090 doi: 10.1109/TFUZZ.2022.3165629
  • 加载中
计量
  • 文章访问数:  17
  • HTML全文浏览量:  4
  • 被引次数: 0
出版历程
  • 收稿日期:  2024-06-18
  • 录用日期:  2024-11-06
  • 网络出版日期:  2024-11-26

目录

    /

    返回文章
    返回