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        模糊多智能體系統(tǒng)的H一致跟蹤控制

        2020-07-07 19:54:53于家鳳李沁生邢文韓春松馮茂巖
        南京信息工程大學學報 2020年3期
        關鍵詞:一致性智能模型

        于家鳳 李沁生 邢文 韓春松 馮茂巖

        摘要

        本文研究非線性多智能體系統(tǒng)在有向拓撲下的領導跟隨H∞一致性問題.首先,提出一種新的多項式模糊建模方法來描述由領導者與跟隨者構建的偏差動態(tài)系統(tǒng).然后,設計一致控制協(xié)議使跟隨者漸近跟蹤領導者的軌跡.基于多項式李雅普諾夫函數(shù)技術,提出松弛的漸近一致的充分條件并確保存在外界干擾時多智能體系統(tǒng)具有H∞抑制性能.將導出的條件轉化為平方和形式并能夠進行數(shù)值求解.最后,給出一個實例來驗證所提出的一致控制協(xié)議的有效性.關鍵詞

        多智能體系統(tǒng);模糊模型;H∞一致性;有向拓撲

        中圖分類號 TP273

        文獻標志碼 A

        0 引言

        T-S模糊模型被認為是能夠以任意精度逼近光滑非線性系統(tǒng)的一個有效工具[1-2],得到了廣泛的關注[3-4].近年來,多項式模糊模型被提出用來建模非線性系統(tǒng)[5],可看作T-S模糊模型的一種推廣.多項式模糊模型得到了廣泛的關注,例如,采用平方和方法的多項式模糊控制系統(tǒng)的控制研究[6-7].

        另一方面,由于多智能體系統(tǒng)廣泛的應用性和顯著的擴展性,多智能體系統(tǒng)的一致問題不斷吸引著研究者們的興趣,包括集群控制、群集控制、編隊控制、復雜網絡同步和通信網絡的擁塞控制[8-9].采用多種控制方法以實現(xiàn)多智能體的一致,例如自適應控制[10-11] 、事件觸發(fā)控制[8,12]、滑??刂芠13]、H∞控制[7,14].特別地,文獻[14]研究了T-S模糊多智能體系統(tǒng)在無向拓撲下的領導跟隨H∞一致控制問題.文獻[7]研究了多項式模糊多智能體系統(tǒng)在無向拓撲下的領導跟隨H∞一致控制問題.為了在模糊模型中處理系統(tǒng)狀態(tài),文獻[7,14]提出了一些嚴格的假設條件.

        受文獻[7,14]啟發(fā),本文研究非線性多智能體系統(tǒng)在有向拓撲下的領導跟隨H∞一致性問題.首先,建立一個多項式模糊模型來描述領導-跟隨構成的非線性多智能體系統(tǒng),去除了文獻[7,14]的一些假設條件.進一步,設計了一個新的控制協(xié)議以確保多智能體系統(tǒng)達到一致.將提出的多項式模糊模型應用于非線性多智能體系統(tǒng)的H∞一致控制問題,即在預設的一個H∞性能指標下,設計一個H∞控制協(xié)議以實現(xiàn)跟隨者和領導者一致.基于多項式李雅普諾夫函數(shù)進行穩(wěn)定性分析,推導出的多項式矩陣不等式條件轉化為平方和(SOS)[15]的條件并進行數(shù)值求解.

        4 結論

        本文研究了有向拓撲下的非線性多智能體系統(tǒng)的H∞一致跟蹤控制問題.首先,提出了一種新的多項式模糊建模方法來描述非線性偏差系統(tǒng),推導出了基于SOS松弛的H∞一致的充分條件.本文所設計的狀態(tài)反饋控制協(xié)議能保證多智能體系統(tǒng)實現(xiàn)漸近一致并滿足設定的干擾抑制H∞性能指標.仿真實例驗證了理論結果的有效性.

        參考文獻

        References

        [1]

        Wang Y,Xia Y,Ahn C K,et al.Exponential stabilization of Takagi-Sugeno fuzzy systems with aperiodic sampling:an aperiodic adaptive event-triggered method[J].IEEE Transactions on Systems,Man,and Cybernetics:Systems,2019,49(2):444-454

        [2] Wu Z G,Xu Y,Lu R,et al.Event-triggered control for consensus of multiagent systems with fixed/switching topologies[J].IEEE Transactions on Systems,Man,and Cybernetics:Systems,2018,48(10):1736-1746

        [3] Fei Z Y,Shi S,Wang T,et al.Improved stability criteria for discrete-time switched T-S fuzzy systems[J].IEEE Transactions on Systems,Man,and Cybernetics:Systems,2019:1-9

        [4] Shi P,Zhang Y,Chadli M,et al.Mixed H-infinity and passive filtering for discrete fuzzy neural networks with stochastic jumps and time delays[J].IEEE Transactions on Neural Networks and Learning Systems,2016,27(4):903-909

        [5] Tanaka K,Yoshida H,Ohtake H,et al.A sum-of-squares approach to modeling and control of nonlinear dynamical systems with polynomial fuzzy systems[J].IEEE Transactions on Fuzzy Systems,2009,17(4):911-922

        [6] Gassara H,El Hajjaji A,Krid M,et al.Stability analysis and memory control design of polynomial fuzzy systems with time delay via polynomial Lyapunov-Krasovskii functional[J].International Journal of Control,Automation and Systems,2018,16(4):2011-2020

        [7] Tabarisaadi P,Mardani M M,Shasadeghi M,et al.A sum-of-squares approach to consensus of nonlinear leader-follower multi-agent systems based on novel polynomial and fuzzy polynomial models[J].Journal of the Franklin Institute,2017,354(18):8398-8420

        [8] 許文盈,曹進德.基于事件驅動機制的多智能體系統(tǒng)協(xié)調控制研究綜述[J].南京信息工程大學學報(自然科學版),2018,10(4):395-400

        XU Wenying,CAO Jinde.An overview of recent progress in the study of event-triggered coordinated schemes of multi-agent systems[J].Journal of Nanjing University of Information Science & Technology (Natural Science Edition),2018,10(4):395-400

        [9] 胡鴻翔,梁錦,溫廣輝,等.多智能體系統(tǒng)的群集行為研究綜述[J].南京信息工程大學學報(自然科學版),2018,10(4):415-421

        HU Hongxiang,LIANG Jin,WEN Guanghui,et al.A survey of development on swarming behavior for multi-agent systems[J].Journal of Nanjing University of Information Science & Technology (Natural Science Edition),2018,10(4):415-421

        [10] Shi P,Shen Q.Observer-based leader-following consensus of uncertain nonlinear multi-agent systems[J].International Journal of Robust and Nonlinear Control,2017,27(17):3794-3811

        [11] Wen G X,Chen C L P,Liu Y,et al.Neural network-based adaptive leader-following consensus control for a class of nonlinear multiagent state-delay systems[J].IEEE Transactions on Cybernetics,2017,47(8):2151-2160

        [12] Zhang H,Yang R,Yan H,et al.H∞consensus of event-based multi-agent systems with switching topology[J].Information Sciences,2016,370/371:623-635

        [13] Zhang J,Lyu M,Shen T,et al.Sliding mode control for a class of nonlinear multi-agent system with time delay and uncertainties[J].IEEE Transactions on Industrial Electronics,2018,65(1):865-875

        [14] Zhao Y,Li B,Qin J,et al.H∞ consensus and synchronization of nonlinear systems based on a novel fuzzy model[J].IEEE Transactions on Cybernetics,2013,43(6):2157-2169

        [15] Prajna S,Papachristodoulou A,Parrilo P A.Introducing SOSTOOLS:a general purpose sum of squares programming solver[C]∥Proceedings of the 41st IEEE Conference on Decision and Control,2002:741-746

        Fuzzy-model-based H∞ consensus tracking

        control of multi-agent systems

        YU Jiafeng1,2 LI Qinsheng1,3 XING Wen4 HAN Chunsong5 FENG Maoyan1

        1 School of Marine & Electrical & Intelligent Engineering,Jiangsu Maritime Institute,Nanjing 211170

        2 School of Electrical and Electronic,The University of Adelaide,Adelaide SA 5005,Australia

        3 School of Mechatronic Engineering and Automation/Shanghai Key Laboratory of

        Power Station Automation Technology,Shanghai University,Shanghai 200072

        4 College of Automation,Harbin Engineering University,Harbin 150001

        5 School of Mechanical and Electrical Engineering,Qiqihar University,Qiqihar 161002

        Abstract This paper is concerned with the H∞ consensus problem for nonlinear leader-follower multi-agent systems (MASs) with a directed communication network.A polynomial fuzzy modeling approach is proposed to describe the error system which is formulated by leader and follower agents.Then,the consensus control protocols are designed for MASs to enforce all the followers to track the trajectory of a leader asymptotically.Based on the polynomial Lyapunov function method,sufficient conditions are presented to ensure the consensus for MASs subject to external disturbances.The obtained conditions are converted into sum of squares and can be numerically solved.Finally,a simulation example is provided to demonstrate the effectiveness of the derived theoretical results.

        Key words multi-agent systems;fuzzy modeling;H∞ consensus;directed topology

        收稿日期 2020-03-02

        資助項目 江蘇省自然科學基金(BK20191457);江蘇省現(xiàn)代教育技術研究課題(61980)重點項目;黑龍江省自然科學基金(F2017028);黑龍江省省屬高等學校基本科研業(yè)務費科研項目(135109242,135409426,135409102)

        作者簡介于家鳳,女,博士,研究方向為模糊控制與復雜動態(tài)網絡系統(tǒng).yyujie99@163.com

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