簡易檢索 / 詳目顯示

回結果列表
研究生： 蔡承宗
Tsai, Cheng-Tzung
論文名稱： 多全向輪無人搬運車之故障偵測與辨識及控制器設計
Fault Detection and Isolation for Multiple Omnidirectional Automated Guided Vehicle and Controller Design
指導教授： 劉彥辰
Liu, Yen-Chen
學位類別： 碩士
Master
系所名稱： 工學院 - 機械工程學系
Department of Mechanical Engineering
論文出版年： 2021
畢業學年度： 109
語文別： 中文
論文頁數： 109
中文關鍵詞： 無人搬運車 、麥可納姆輪 、馬達失效 、故障檢測 、陣形控制
外文關鍵詞： Automated guided vehicles, motor failure, fault detection and isolation, formation control, cooperative transportation
相關次數： 點閱：93  下載：34 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • 無人搬運車已被廣泛的使用於貨物搬運在現代化的工廠中，提高了工廠中的工作效率。但無人搬運車在搬運過程中容易因過度使用或負載過重而發生故障，例如感測器故障、車體結構損壞、馬達失效等。其中有些故障造成的影響非常巨大且快速，例如當搬運過程中馬達發生故障，會使控制器無法正常控制無人搬運車，導致無人搬運車跑離預期路線而影響其他工廠中的機台。在過去的研究中，故障偵測、辨識與重建控制器(Fault Detection and Isolation Recon figuration, FDIR) 常用於解決故障問題；傳統FDIR分為三個步驟，首先是偵測無人搬運車是否故障發生；由於不同的故障來源有許多種，因此第二步驟為辨識無人搬運車上所發生的故障種類；最後一步則是根據辨識的故障結果調整控制器，使無人搬運車在故障狀態下仍可持續執行任務。由於目前使用的FDIR需要知道準確系統的參數，這個使用條件相當難在工廠中達成。此外，工廠中經常用多台無人搬運車進行大型物體的協同搬運，若有其中一台無人搬運車發生故障或遭受強大外在干擾時，便容易造成隊形破壞，使物體從無人搬運車上掉落。因此，本研究改善過去的FDIR方法，針對多無人搬運車合作搬運任務加入適應性控制來估測無人搬運車參數，以提升故障偵測及辨識的效能。此外，本論文同時在控制器中加入陣形控制，使無人搬運車間藉由互溝通與參數調節，讓陣形變得更穩定，使無人搬運車在故障狀態下仍可完成搬運任務。

    AGV systems have been utilized widely on cooperative transporting large and heavy objects in factory or logistic to reduce the demands on human workers for the sake of increasing efficiency and reducing cost. However, the presence of uncertain faults on driving motors could degrades the transportation process and cause danger during operation. In this paper, a three-step Fault Detection Isolation Reconfi guration (FDIR) is proposed to ensure that the tracking/transportation mission can be completed in the presence of unknown actuator faults. In the first step, an observer is designed for an AGV to determine whether a fault has occurred or not, while the second step utilizes a bank of observers to determine the type of fault. The third step involves reconfiguring the controller according to the isolation results. In the proposed approach, the FDIR method is addressed in the presence of dynamic uncertainties for both detection and isolation, that make the proposed approach superior to the previously developed method. In addition, during cooperative transportation if one of AGV fails, the formation will be damaged and cause objects to fall from the AGV. Therefore, we design the distributed formation controller let the AGVs can communicate with each other to stabilize the formation. Finally the simulation and experiment results are presented to illustrate the proposed FDIR method and controller for multiple omnidirectional AGV systems.

    摘要 i 英文延長摘要 ii 誌謝 xiii 目錄 xiv 圖目錄 xvii 表目錄 xix 符號表 xx 第一章 緒論 1 1.1 研究背景 1 1.1.1 無人搬運車 1 1.1.2 協同搬運與控制器設計 3 1.1.3 故障檢測 5 1.2 文獻回顧 7 1.3 研究動機與目的 9 1.4 研究目標與貢獻 11 1.5 論文架構 12 第二章 基礎理論 14 2.1 Lyapunov穩定性 14 2.1.1 非線性系統 14 2.1.2 非線性系統穩定性 15 2.1.3 Lyapunov函數與基本定理 15 2.1.4 Barbalat’s Lemma 17 2.2 觀測器原理 18 2.2.1 線性系統模型 18 2.2.2 線性系統觀測器設計 18 2.3 滑動模式控制 20 2.3.1 滑動模式控制 20 2.3.2 適應性控制 22 2.4 陣形控制 23 2.4.1 陣形追蹤控制器 23 2.5 圖形理論 24 第三章 無人搬運車模型 30 3.1 無人搬運車結構 30 3.1.1 車體結構 30 3.1.2 旋轉平台 31 3.2 無人搬運車動力模型 36 3.3 協同搬運系統 44 第四章 故障偵測與辨識 45 4.1 系統架構 45 4.2 故障偵測 47 4.2.1 觀測器設計 47 4.2.2 穩定性證明 48 4.2.3 故障偵測標準 49 4.3 故障辨識 50 4.3.1 觀測器設計 50 4.3.2 穩定性證明 53 4.3.3 故障馬達辨別 54 4.4 控制器重建 55 4.5 模擬結果與討論 56 第五章 陣形維持控制器 68 5.1 控制器設計 68 5.2 穩定性證明 71 5.3 模擬結果與討論 73 第六章 實驗架構與結果 80 6.1 實驗設備 80 6.1.1 全向輪無人搬運車 80 6.1.2 機器人作業系統 80 6.1.3 外部定位系統 81 6.2 實驗流程 82 6.3 實驗結果與討論 84 6.3.1 實驗一：無故障發生 85 6.3.1 實驗二：FDIR與陣形維持控制器之效能 89 6.3.3 實驗三：無陣形維持控制器之效能 97 6.3.4 實驗四：FDIR於馬達失去效率之效能 101 6.3.5 實驗結果與討論 102 第七章 結論與未來展望 103 7.1 結論 103 7.1.1 故障偵測與辨識 103 7.1.2 陣形維持控制器 103 7.2 未來展望 104 參考文獻 105

    [1] Delta Brand News. Delta demonstrates smart agv distribution solution with high-efficiency numeral control and data management. https://brandnews. deltaww.com/EN/36/SpecialTopic.aspx, Nov 2017.
    [2] Bart Stouten and Aart-Jan de Graaf. Cooperative transportation of a large object-development of an industrial application. In IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA'04. 2004, volume 3, pages 2450-2455. IEEE, 2004.
    [3] Ling Qiu, Wen-Jing Hsu, Shell-Ying Huang, and Han Wang. Scheduling and routing algorithms for agvs: a survey. International Journal of Production Research, 40(3):745-760, 2002.
    [4] Hamed Fazlollahtabar and Mohammad Saidi-Mehrabad. Methodologies to optimize automated guided vehicle scheduling and routing problems: a review study. Journal of Intelligent & Robotic Systems, 77(3):525–545, 2015.
    [5] Elio Tuci, Muhanad HM Alkilabi, and Otar Akanyeti. Cooperative object transport in multi-robot systems: A review of the state-of-the-art. Frontiers in Robotics and AI, 5:59, 2018.
    [6] Alpaslan Yufka and Metin Ozkan. Formation-based control scheme for cooperative transportation by multiple mobile robots. International Journal of Advanced Robotic Systems, 12(9):120, 2015.
    [7] Mohamed A Kamel, Youmin Zhang, and Xiang Yu. Fault-tolerant cooperative control of multiple wheeled mobile robots under actuator faults. IFAC- PapersOnLine, 48(21):1152-1157, 2015.
    [8] Mohamed A Kamel, Xiang Yu, and Youmin Zhang. Formation control and coordination of multiple unmanned ground vehicles in normal and faulty situations: A review. Annual reviews in control, 49:128-144, 2020.
    [9] J Gertler. Failure detection and isolation in complex process plants a survey. In Microcomputer Application in Process Control, pages 13-23. Elsevier, 1987.
    [10] Hao Ren, Yan Lin, and Gang Zhu. Adaptive compensation for miso nonlinear systems against actuator failures. In 2018 IEEE 4th International Conference on Control Science and Systems Engineering (ICCSSE), pages 351-355. IEEE, 2018.
    [11] Hamidreza Modares, Bahare Kiumarsi, Frank L Lewis, Frank Ferrese, and Ali Davoudi. Resilient and robust synchronization of multiagent systems under attacks on sensors and actuators. IEEE transactions on cybernetics, 50(3):1240-1250, 2019.
    [12] Ahmad M Alshorman, Omar Alshorman, Muhammad Irfan, Adam Glowacz, Fazal Muhammad, and Wahyu Caesarendra. Fuzzy-based fault-tolerant control for omnidirectional mobile robot. Machines, 8(3):55, 2020.
    [13] Elias N Skoundrianos and Spyros G Tzafestas. Finding fault-fault diagnosis on the wheels of a mobile robot using local model neural networks. IEEE Robotics & Automation Magazine, 11(3):83-90, 2004.
    [14] Inseok Hwang, Sungwan Kim, Youdan Kim, and Chze Eng Seah. A survey of fault detection, isolation, and reconfi guration methods. IEEE transactions on control systems technology, 18(3):636-653, 2009.
    [15] Maryam Abdollahi. Simultaneous sensor and actuator fault detection, isolation and estimation of nonlinear euler-lagrange systems using sliding mode observers. In 2018 IEEE Conference on Control Technology and Applications (CCTA), pages 392{397. IEEE, 2018.
    [16] Yong Chen, Jianhui Zhi, Xinmin Dong, Li Zhao, and Yali Chen. Robust adaptive fault estimation for a class of over-actuated systems with loss of e ffectiveness actuator faults. In 2018 37th Chinese Control Conference (CCC), pages 5919-5923. IEEE, 2018.
    [17] Alessandro Casavola and Emanuele Garone. Fault-tolerant adaptive control allocation schemes for overactuated systems. International Journal of Robust and Nonlinear Control, 20(17):1958-1980, 2010.
    [18] Martin L Leuschen, Ian D Walker, and Joseph R Cavallaro. Fault residual generation via nonlinear analytical redundancy. IEEE transactions on control systems technology, 13(3):452-458, 2005.
    [19] Kamel Bouibed, Abdel Aitouche, and Mireille Bayart. Sensor and actuator fault detection and isolation using two model based approaches: Application to an autonomous electric vehicle. In 18th Mediterranean Conference on Control and Automation, MED'10, pages 1290-1295. IEEE, 2010.
    [20] Jie Su, Jianping He, Peng Cheng, and Jiming Chen. Actuator fault diagnosis of a hexacopter: A nonlinear analytical redundancy approach. In 2017 25th Mediterranean Conference on Control and Automation (MED), pages 413-418. IEEE, 2017.
    [21] Andrea Cristofaro and Tor Arne Johansen. Fault-tolerant control allocation: an unknown input observer based approach with constrained output fault directions. In 52nd IEEE Conference on Decision and Control, pages 3818-3824. IEEE, 2013.
    [22] Andrea Cristofaro and Tor Arne Johansen. Fault tolerant control allocation using unknown input observers. Automatica, 50(7):1891-1897, 2014.
    [23] Mirza Tariq Hamayun, Christopher Edwards, and Halim Alwi. A fault tolerant control allocation scheme with output integral sliding modes. Automatica, 49(6):1830-1837, 2013.
    [24] Hamid Taheri, Bing Qiao, and Nurallah Ghaeminezhad. Kinematic model of a four mecanum wheeled mobile robot. International journal of computer applications, 113(3):6-9, 2015.
    [25] Kyung-Lyong Han, Oh-Kyu Choi, Jinwook Kim, Hyosin Kim, and Jin S Lee. Design and control of mobile robot with mecanum wheel. In 2009 ICCASSICE, pages 2932-2937. IEEE, 2009.
    [26] Patrick F Muir and Charles P Neuman. Kinematic modeling of wheeled mobile robots. Journal of robotic systems, 4(2):281-340, 1987.
    [27] Robert L Williams, Brian E Carter, Paolo Gallina, and Giulio Rosati. Dynamic model with slip for wheeled omnidirectional robots. IEEE transactions on Robotics and Automation, 18(3):285-293, 2002.
    [28] Jih-Sien Peng and Yen-Chen Liu. Towards cooperative transportation of multiple mecanum-wheeled automated guided vehicles. In ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers Digital Collection, 2019.
    [29] Swati Mishra, Mukesh Sharma, and Santhakumar Mohan. Behavioural fault tolerant control of an omni directional mobile robot with four mecanum wheels. Defence Science Journal, 69(4):353, 2019.
    [30] Jaydev P Desai, Jim Ostrowski, and Vijay Kumar. Controlling formations of multiple mobile robots. In Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No. 98CH36146), volume 4, pages 2864-2869. IEEE, 1998.
    [31] Jinwei Yu, Jinchen Ji, Zhonghua Miao, and Jin Zhou. Adaptive formation control of networked lagrangian systems with a moving leader. Nonlinear Dynamics, 90(4):2755-2766, 2017.
    [32] Jie Mei, Wei Ren, and Guangfu Ma. Distributed coordinated tracking with a dynamic leader for multiple euler-lagrange systems. IEEE Transactions on Automatic Control, 56(6):1415-1421, 2011.
    [33] Jawhar Ghommam, Hasan Mehrjerdi, Maarouf Saad, and Faical Mnif. Formation path following control of unicycle-type mobile robots. Robotics and Autonomous Systems, 58(5):727-736, 2010.
    [34] Firhan Huzaefa and Yen-Chen Liu. Centralized control architecture for cooperative object transportation using multiple omnidirectional agvs. In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 6526{6532. IEEE, 2019.
    [35] Wei Wang and Changyun Wen. Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance. Automatica, 46(12):2082-2091, 2010.
    [36] Xiaodong Zhang, Marios M Polycarpou, and Thomas Parisini. A robust detection and isolation scheme for abrupt and incipient faults in nonlinear systems. IEEE transactions on automatic control, 47(4):576-593, 2002.
    [37] Andrea Cristofaro, Marios M Polycarpou, and Tor Arne Johansen. Fault-tolerant control allocation for overactuated nonlinear systems. Asian Journal of Control, 20(2):621-634, 2018.
    [38] Abbas Chamseddine, Youmin Zhang, and Camille Alain Rabbath. Trajectory planning and re-planning for fault tolerant formation
    flight control of quadrotor unmanned aerial vehicles. In 2012 American Control Conference (ACC), pages 3291-3296. IEEE, 2012.
    [39] Iman Saboori and Khashayar Khorasani. Actuator fault accommodation strategy for a team of multi-agent systems subject to switching topology. Automatica, 62:200-207, 2015.
    [40] Huiliao Yang, Bin Jiang, Hao Yang, and Ke Zhang. Cooperative control reconfi guration in multiple quadrotor systems with actuator faults. IFAC- PapersOnLine, 48(21):386-391, 2015.
    [41] 張廣奇and 趙勇. Agv 系統自動化立体倉庫常見故障排除方法. 設備管理與維修, 1, 2016.
    [42] Khalil Hassan. Khalil, nonlinear systems. Prentice-Hall, Inc., New Jersey, 1996.
    [43] Jean-Jacques E Slotine, Weiping Li, et al. Applied nonlinear control, volume 199. Prentice hall Englewood Cli s, NJ, 1991.
    [44] Mark French, Csaba Szepesvari, and Eric Rogers. Performance of nonlinear approximate adaptive controllers. John Wiley & Sons, 2003.
    [45] Bruno Siciliano and Oussama Khatib. Springer handbook of robotics. springer, 2016.
    [46] Mark W Spong, Seth Hutchinson, Mathukumalli Vidyasagar, et al. Robot modeling and control, volume 3. wiley New York, 2006.
    [47] Douglas Brent West et al. Introduction to graph theory, volume 2. Prentice hall Upper Saddle River, 2001.
    [48] C. Godsil and G. F. Royle. Algebraic Graph Theory. Springer, 2001.
    [49] Lih-Chang Lin and Hao-Yin Shih. Modeling and adaptive control of an omnimecanum-wheeled robot. 2013.
    [50] Kyung-Lyong Han, Hyosin Kim, and Jin S Lee. The sources of position errors of omni-directional mobile robot with mecanum wheel. In 2010 IEEE International Conference on Systems, Man and Cybernetics, pages 581-586. IEEE, 2010.

    下載圖示 校內：立即公開
    校外：立即公開
    QR CODE