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研究生： 邱富信
Fu-Hsin Chiu
論文名稱： 多自主式移動機器人之行為協調及網絡控制系統
Autonomous Behavior Coordination and Networked Control System among Multiple Mobile Robots
指導教授： 李敏凡
Min-Fan Ricky Lee
口試委員: 蔡明忠
Ming-Jong Tsai
郭重顯
Chung-Hsien Kuo
羅仁權
Ren C. Luo
陳美勇
Mei-Yung Chen
黃正自
Jeng-Tze Huang
學位類別： 博士
Doctor
系所名稱： 工程學院 - 自動化及控制研究所
Graduate Institute of Automation and Control
論文出版年： 2014
畢業學年度： 103
語文別： 英文
論文頁數： 166
中文關鍵詞： 行為協調控制 、粒子群聚最佳化演算法 、群體式機器人 、多目標優化演算法 、網路控制系統 、時間延遲 、約束性機器人系統
外文關鍵詞： Behavior Coordination Control, Particle swarm optimization (PSO), Swarm robotics, Multi-objective optimization, Networked Control System, Network Delay, Non-holonomic system
相關次數： 點閱：492  下載：15 
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    • 經由協調之多移動機器人系統較單一機器人系統具有顯著的優勢，特別是在處理特定任務時提供很好的強健性、良好的適應性及可擴展性。本論文提出基於行為的控制架構，可用於實現運行此多機器人系統於複雜的真實環境以完成更高層次的目標。然而，如何選擇適當的行為及協調機器人之間的互動仍是一大挑戰。此外，控制器與多機器人系統之通訊時間延遲亦會影響系統之性能及穩定性。有了這些限制，使得有效地分配任務的機器人變得困難。
    因此本論文第二章著重於協調移動機器人不同的自主式行為，並針對 “偵傁與災難救援”之場景提出以粒子群聚優化演算法（PSO）之行為協調控制器。其中一個移動機器人扮演領航角色來引導跟隨機器人通過尋找遇難者的所在區域，協同搬運或提供即時緊急援助。藉由優化之粒子群最佳化演算法，各機器人之每一個行為將簡化為單位向量，然後通過模擬與實驗驗證，整合最佳參數來實現多機器人之協調與互動。此外，為了解決機器人之間軌跡追蹤通信延遲的問題，於第四章亦提出狀態估計與預測狀結構的延遲補償演算法。
    為了進一步研究此系統之強健性，分別對系統中出現時間延遲、複雜環境以及演算法參數優化進行模擬與真實實驗。綜合以上所述，本文針對行為協調、通訊延遲進行研究，主要工作著眼於不同外界環境中群體協同行為控制策略的設計，並提出降低時間延遲之估測狀態器的設計，其模擬及實驗結果驗證了所提演算法的有效性。本文提出之行為協調控制器具有很好的強健性、所提出解決通信延遲之狀態估計器亦顯示其可行性並能夠穩定系統和用於補償時間延遲的不利影響。

    A coordinated multiple mobile robots provide advance awareness, high fault tolerance than single robot when dealing specific mission. Behavior-based control architecture can be used to achieve higher level goals without modeling complex, real-world environment. However, the difficulty is how to select the proper behaviors for robustness and efficiency in accomplishing goals. Besides, the time-delay affects the system due to the fact that the controller and mobile robot are linked via a delay inducing communication channel, by which the performance and stability of the system are possibly compromised. With these constraints, allocating tasks efficiently to robots become difficult.
    This dissertation focuses on the study of coordination of different autonomous steering behavior for mobile robots. The targeted scenario is "Assistance and Rescue Disaster", where a mobile robot is used to steer through a hazardous site in search of victims, in order to provide them rescue or emergency assistance. Coordinated various behavior for multiple mobile robots is implemented through the modified Particle Swarm Optimization (PSO) algorithm, which treats each behavior as force vector then through intense simulation and experiment to find the best parameter to integrated each behavior. Additionally, in order to tackle communicate delay problem, a state estimator with a predictor-like structure for delay compensation is proposed.
    Therefore, by considering constraint function for PSO algorithm and state estimator for communicate delay, the proposed system is able to show the feasibility and is capable of stabilizing the system and compensates for the negative effects of the time-delay. Experimental and numerical results are given to demonstrate the applicability and guaranteed up to a maximum admissible time-delay of the proposed system.

    中文摘要 III Acknowledgement V Table of Contents VI List of Figures X List of Tables XV Chapter 1 Introduction 1 1.1 Behavior-based robotics 6 1.2 Behavior coordination mechanisms 7 1.3 Communications infrastructure 7 1.4 Integration of Techniques 8 1.5 Research Goals and Contribution 10 1.6 Dissertation Structure 10 Chapter 2 Optimization Theory for behavior coordination 13 2.1 Steering Behaviors 19 2.1.1 Position, Velocity and Movement 23 2.1.2 Calculating Forces 24 2.1.3 Dynamics of differenctial-drive wheeled mobiel robot 26 2.2 Classical Optimization Methods 37 2.3 Evolutionary Algorithms (EAs) 41 2.3.1 Evolution Strategy (ES) 42 2.3.2 Genetic Algorithms (GA) 42 2.3.3 Particle Swarm Optimization (PSO) 43 Chapter 3 Modified PSO Behavioral Coordinate Controller for Multi-robot collaboration system 52 3.1 Introduction 52 3.2 Method 54 3.2.1 Path Planning Behavior 55 3.2.2 Obstacle Avoidance Behavior 56 3.2.3 Formation Keeping Behavior 56 3.2.4 Target Tracking Behavior 58 3.2.5 Modified PSO Behavior Control Architecture 60 3.3 Results 66 3.3.1 Offline simulation 67 3.3.2 Online experiments 69 3.4 Summary 74 Chapter 4 Generalized Predictive Control in a Wireless Networked Control System 76 4.1 Introduction 77 4.2 Method 80 4.2.1 Tracking controller – No time delay 80 4.2.2 Tracking controller – With time delay 85 4.3 Formulation of GPC 88 4.3.1 GPC Control Strategy 92 4.3.2 GPC in State-Space Formulation 93 4.3.3 State Estimator 98 4.4 Results 101 4.4.1 Predictor-based Control of a mobile robot with delays 101 4.4.2 GPC implementation in WiNCS 104 4.4.3 Latency and throughput on actual Wireless Network Environment 106 4.4.4 System Response with Random Delay and Packets Loss 110 4.4.5 System Response with Networked-Induced Delay in NS2 111 4.5 Discussion 117 4.6 Summary 119 Chapter 5 Applying Modified PSO in Experiment 121 5.1 Optimization Simulation Results 121 5.1.1 Simple Environment 121 5.1.2 Complex Laboratory Scenario 132 5.2 Real Environemnet Scenario 135 Chapter 6 Conclusions and Future Work 137 6.1 Contributions and Significance 138 6.2 Possible Future Work 139 References 140 Appendix 148

    [1] A. Das, J. Spletzer, V. Kumar, and C. Taylor, "A Distributed Multi-Robot System for Cooperative Manipulation," in Multi-Robot Systems: From Swarms to Intelligent Automata, ed: Springer Netherlands, 2002, pp. 93-100.
    [2] A. Campbell and A. S. Wu, "Multi-agent role allocation: Issues, approaches, and multiple perspectives," Autonomous Agents and Multi-Agent Systems, vol. 22, pp. 317-355, 2011.
    [3] G. A. Hollinger and S. Singh, "Multirobot Coordination With Periodic Connectivity: Theory and Experiments," Robotics, IEEE Transactions on, vol. 28, pp. 967-973, 2012.
    [4] S. Martinez, J. Cortes, and F. Bullo, "Motion Coordination with Distributed Information," Control Systems, IEEE, vol. 27, pp. 75-88, 2007.
    [5] F. Pasqualetti, A. Franchi, and F. Bullo, "On Cooperative Patrolling: Optimal Trajectories, Complexity Analysis, and Approximation Algorithms," Robotics, IEEE Transactions on, vol. 28, pp. 592-606, 2012.
    [6] K. Tumer and S. Proper, "Coordinating actions in congestion games: impact of top–down and bottom–up utilities," Autonomous Agents and Multi-Agent Systems, vol. 27, pp. 419-443, 2013/11/01 2013.
    [7] P. B. Sujit, A. Sinha, and D. Ghose, "Multiple UAV task allocation using negotiation," presented at the Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems, Hakodate, Japan, 2006.
    [8] M. Snel and S. Whiteson, "Learning potential functions and their representations for multi-task reinforcement learning," Autonomous Agents and Multi-Agent Systems, pp. 1-45, 2013/09/05 2013.
    [9] A. Winfield, W. Liu, J. Nembrini, and A. Martinoli, "Modelling a wireless connected swarm of mobile robots," Swarm Intelligence, vol. 2, pp. 241-266, 2008.
    [10] L. C. A. Pimenta, G. A. S. Pereira, N. Michael, R. C. Mesquita, M. M. Bosque, L. Chaimowicz, et al., "Swarm Coordination Based on Smoothed Particle Hydrodynamics Technique," Robotics, IEEE Transactions on, vol. 29, pp. 383-399, 2013.
    [11] I. Navarro and F. Matia, "An Introduction to Swarm Robotics," ISRN Robotics, vol. 2013, p. 10, 2013.
    [12] M. Brambilla, E. Ferrante, M. Birattari, and M. Dorigo, "Swarm robotics: a review from the swarm engineering perspective," Swarm Intelligence, vol. 7, pp. 1-41, 2013/03/01 2013.
    [13] R. Wei and R. W. Beard, "Consensus seeking in multiagent systems under dynamically changing interaction topologies," Automatic Control, IEEE Transactions on, vol. 50, pp. 655-661, 2005.
    [14] R. Olfati-Saber and R. M. Murray, "Consensus problems in networks of agents with switching topology and time-delays," Automatic Control, IEEE Transactions on, vol. 49, pp. 1520-1533, 2004.
    [15] R. Olfati-Saber, J. A. Fax, and R. M. Murray, "Consensus and Cooperation in Networked Multi-Agent Systems," Proceedings of the IEEE, vol. 95, pp. 215-233, 2007.
    [16] K. S. Decker, "Distributed problem-solving techniques: A survey," Systems, Man and Cybernetics, IEEE Transactions on, vol. 17, pp. 729-740, 1987.
    [17] G. Dudek, M. M. Jenkin, E. Milios, and D. Wilkes, "A taxonomy for multi-agent robotics," Autonomous Robots, vol. 3, pp. 375-397, 1996/12/01 1996.
    [18] R. Rocha, "Fostering Cooperation among Intelligent Machines," 2002.
    [19] W. G. Walter, "An Imitation of Life," Scientific American, pp. 42-45, May 1950.
    [20] R. C. Arkin, "Motor schema based navigation for a mobile robot: An approach to programming by behavior," in Robotics and Automation. Proceedings. 1987 IEEE International Conference on, 1987, pp. 264-271.
    [21] T. L. Huntsberger, A. Trebi-Ollennu, H. Aghazarian, P. S. Schenker, P. Pirjanian, and H. D. Nayar, "Distributed Control of Multi-Robot Systems Engaged in Tightly Coupled Tasks," Autonomous Robots, vol. 17, pp. 79-92, 2004.
    [22] T. Huntsberger and G. Woodward, "Intelligent autonomy for unmanned surface and underwater vehicles," in MTS/IEEE Kona Conference, OCEANS'11, Kona, HI, 2011.
    [23] T. Balch and R. C. Arkin, "Behavior-based formation control for multirobot teams," Robotics and Automation, IEEE Transactions on, vol. 14, pp. 926-939, 1998.
    [24] F. Driewer, H. Baier, and K. Schilling, "Robot–human rescue teams: a user requirements analysis," Advanced Robotics, vol. 19, pp. 819-838, 2005/01/01 2005.
    [25] D. S. Katz and R. R. Some, "NASA advances robotic space exploration," Computer, vol. 36, pp. 52-61, 2003.
    [26] N. Xiong, J. He, Y. Yang, Y. He, T.-H. Kim, and C. Lin, "A survey on decentralized flocking schemes for a set of autonomous mobile robots," Journal of Communications, vol. 5, pp. 31-38, 2010.
    [27] A. Brutschy, G. Pini, C. Pinciroli, M. Birattari, and M. Dorigo, "Self-organized task allocation to sequentially interdependent tasks in swarm robotics," Autonomous Agents and Multi-Agent Systems, pp. 1-25, 2012/12/01 2012.
    [28] R. C. Arkin, "Motor schema-based mobile robot navigation," International Journal of Robotics Research, vol. 8, pp. 92-112, 1989.
    [29] R. Roberts, C. Pippin, and T. Balch, "Learning outdoor mobile robot behaviors by example," Journal of Field Robotics, vol. 26, pp. 176-195, 2009.
    [30] R. Huq, R. Gosine, and G. Mann, "An integrated approach for multilane robot motion planning using motor schema and fuzzy logic," in 2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004, October 10, 2004 - October 13, 2004, The Hague, Netherlands, 2004, pp. 5301-5306.
    [31] M. B. Dias, R. Zlot, N. Kalra, and A. Stentz, "Market-Based Multirobot Coordination: A Survey and Analysis," Proceedings of the IEEE, vol. 94, pp. 1257-1270, 2006.
    [32] R. Byeong-Soon and Y. Hyun Seung, "Integration of reactive behaviors and enhanced topological map for robust mobile robot navigation," Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, vol. 29, pp. 474-485, 1999.
    [33] M. F. R. Lee and F. H. S. Chiu, "A fuzzy logic navigated service mobile robot," in Fuzzy Theory and Its Applications (iFUZZY), 2013 International Conference on, 2013, pp. 183-188.
    [34] M. F. R. Lee, H. Nguyen The, and F. H. S. Chiu, "An autonomous mobile robot for indoor security patrol," in Fuzzy Theory and Its Applications (iFUZZY), 2013 International Conference on, 2013, pp. 189-194.
    [35] R. A. Brooks, "Intelligence without reason," in Proceedings of the 12th International Joint Conference on Artificial Intelligence. Part 1 (of 2), Aug 24 - 30 1991, Sydney, Aust, 1991, pp. 569-569.
    [36] C. W. Reynolds, "Steering behaviors for autonomous characters," Game developers conference, vol. 1999, pp. 763-782, 1999.
    [37] N. T. H. Min-Fan Ricky Lee, "Aerial Visual Aid System for Ground Mobile Robot Behavior Controller in Joint Operation," in Fuzzy Theory and it's Applications (iFUZZY), 2013 International Conference on, 2013, pp. 201-206.
    [38] W. Ren, Beard, Randal, "Decentralized Behavioral Approach to Wheeled Mobile Robot Formation Maneuvers," in Distributed Consensus in Multi-vehicle Cooperative Control, ed: Springer London, 2008, pp. 207-223.
    [39] D. V. Dimarogonas and K. J. Kyriakopoulos, "Connectedness Preserving Distributed Swarm Aggregation for Multiple Kinematic Robots," Robotics, IEEE Transactions on, vol. 24, pp. 1213-1223, 2008.
    [40] A. Howard, M. Matarić, and G. Sukhatme, "Mobile Sensor Network Deployment using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem," in Distributed Autonomous Robotic Systems 5, H. Asama, T. Arai, T. Fukuda, and T. Hasegawa, Eds., ed: Springer Japan, 2002, pp. 299-308.
    [41] H. Zhang and J. P. Ostrowski, "Visual motion planning for mobile robots," IEEE Transactions on Robotics and Automation, vol. 18, pp. 199-208, April 2002.
    [42] N. Sariff and N. Buniyamin, "An Overview of Autonomous Mobile robot Path Planning Algorithms," in SCOReD 4th Student Conf. Research and Development, 2006, pp. 183-188.
    [43] G. B. Dantzig, Linear Programming and Extensions: Princeton University Press, 1998.
    [44] J. Yaochu and J. Branke, "Evolutionary optimization in uncertain environments-a survey," Evolutionary Computation, IEEE Transactions on, vol. 9, pp. 303-317, 2005.
    [45] T. Baeck, U. Hammel, and H.-P. Schwefel, "Evolutionary computation: Comments on the history and current state," IEEE Transactions on Evolutionary Computation, vol. 1, pp. 3-17, 1997.
    [46] K. M. Elsayed and H. G. Perros, "On the Effective Bandwidth of Arbitrary on/off Sources," in Data Communications and their Performance, S. Fdida and R. Onvural, Eds., ed: Springer US, 1996, pp. 257-271.
    [47] F. O. Karray and C. W. De Silva, Soft Computing and Intelligent Systems Design: Theory, Tools, and Applications: Pearson/Addison Wesley, 2004.
    [48] K. Kameyama, "Particle swarm optimization - A survey," IEICE Transactions on Information and Systems, vol. E92-D, pp. 1354-1361, 2009.
    [49] R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Micro Machine and Human Science, 1995. MHS '95., Proceedings of the Sixth International Symposium on, 1995, pp. 39-43.
    [50] J. Kennedy, "The particle swarm: social adaptation of knowledge," in Evolutionary Computation, 1997., IEEE International Conference on, 1997, pp. 303-308.
    [51] S. Yuhui and R. Eberhart, "A modified particle swarm optimizer," in Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on, 1998, pp. 69-73.
    [52] L. Davis, Handbook of genetic algorithms: Van Nostrand Reinhold, 1991.
    [53] E. Masehian and D. Sedighizadeh, "A multi-objective PSO-based algorithm for robot path planning," in Industrial Technology (ICIT), 2010 IEEE International Conference on, 2010, pp. 465-470.
    [54] O. Yeniay, "Penalty function methods for constrained optimization with genetic algorithms," Mathematical and Computational Applications, vol. 10, pp. 45-56, 2005.
    [55] Z. Michalewicz and M. Schmidt, "Evolutionary Algorithms and Constrained Optimization," in Evolutionary Optimization. vol. 48, ed: Springer US, 2002, pp. 57-86.
    [56] F.-H. S. C. Min-Fan Ricky Lee, and Chen Zhuo, "Remote Sensing and Analysis using Autonomous Mobile Robot with onboard Micro-Spectrometer," in Fuzzy Theory and it's Applications (iFUZZY), 2012 International Conference on, 2013.
    [57] T. Fukuda, I. Takagawa, and Y. Hasegawa, "From intelligent robot to multi-agent robotic system," in Integration of Knowledge Intensive Multi-Agent Systems, 2003. International Conference on, 2003, pp. 413-417.
    [58] M. J. Mataric, G. S. Sukhatme, and E. H. Ostergaard, "Multi-robot task allocation in uncertain environments," Autonomous Robots, vol. 14, pp. 255-263, 2003.
    [59] M. Yan and G. Jing, "A distributed swarm intelligence based algorithm for a cooperative multi-robot construction task," in Swarm Intelligence Symposium, 2008. SIS 2008. IEEE, 2008, pp. 1-6.
    [60] S. Dong, W. Can, S. Wen, and F. Gang, "A Synchronization Approach to Trajectory Tracking of Multiple Mobile Robots While Maintaining Time-Varying Formations," Robotics, IEEE Transactions on, vol. 25, pp. 1074-1086, 2009.
    [61] J. P. Desai, J. P. Ostrowski, and V. Kumar, "Modeling and control of formations of nonholonomic mobile robots," Robotics and Automation, IEEE Transactions on, vol. 17, pp. 905-908, 2001.
    [62] A. L. F. Perez, G. Bittencourt, and M. Roisenberg, "Embodied Evolution with a New Genetic Programming Variation Algorithm," in Autonomic and Autonomous Systems, 2008. ICAS 2008. Fourth International Conference on, 2008, pp. 118-123.
    [63] A. Prieto, F. Bellas, and R. Duro, "Adaptively Coordinating Heterogeneous Robot Teams through Asynchronous Situated Coevolution Neural Information Processing." vol. 5864, C. Leung, M. Lee, and J. Chan, Eds., ed: Springer Berlin / Heidelberg, 2009, pp. 75-82.
    [64] H. Feifei, W. Long, W. Qining, W. Ming, and J. Yingmin, "Coordinated control of multiple mobile robots in pursuit-evasion games," in American Control Conference, 2009. ACC '09., 2009, pp. 2861-2866.
    [65] C. Fu-Hsin, "Analysis and Control of Cooperative Behavior Architecture for Multiple Autonomous Mobile Robots," Master of Science, Graduate Institute of Automation and Control (GIAC), National Taiwan University of Science and Technology, Taipei, 2009.
    [66] H. Kao-Shing, C. Yu-Jen, and W. Chun-Ju, "Fusion of Multiple Behaviors Using Layered Reinforcement Learning," Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, vol. 42, pp. 999-1004, 2012.
    [67] L. Feng and Y. Hao, "Modeling and control of fuzzy discrete event systems," Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 32, pp. 408-415, 2002.
    [68] Q. Zhihua, W. Jing, and R. A. Hull, "Cooperative Control of Dynamical Systems With Application to Autonomous Vehicles," Automatic Control, IEEE Transactions on, vol. 53, pp. 894-911, 2008.
    [69] M.-F. R. Lee and K. H.-E. Lee, "Autonomous target tracking and following mobile robot," Journal of the Chinese Institute of Engineers, vol. 36, pp. 502-529, 2013/06/01 2013.
    [70] S. Kitayama, M. Arakawa, and K. Yamazaki, "Penalty function approach for the mixed discrete nonlinear problems by particle swarm optimization," Structural and Multidisciplinary Optimization, vol. 32, pp. 191-202, 2006/09/01 2006.
    [71] Z. Wei, M. S. Branicky, and S. M. Phillips, "Stability of networked control systems," Control Systems Magazine, IEEE, vol. 21, pp. 84-99, 2001.
    [72] Y. Tipsuwan and M.-Y. Chow, "Control methodologies in networked control systems," Control Engineering Practice, vol. 11, pp. 1099-1111, 2003.
    [73] W. L. D. Leung, R. Vanijjirattikhan, L. Zheng, X. Le, T. Richards, B. Ayhan, et al., "Intelligent space with time sensitive applications," in Advanced Intelligent Mechatronics. Proceedings, 2005 IEEE/ASME International Conference on, 2005, pp. 1413-1418.
    [74] F.-Y. Wang and D. Liu. (2008). Networked Control Systems:Theory and Applications.
    [75] G. C. Walsh, O. Beldiman, and L. Bushnell, "Asymptotic behavior of networked control systems," in Control Applications, 1999. Proceedings of the 1999 IEEE International Conference on, 1999, pp. 1448-1453 vol. 2.
    [76] G. C. Walsh, Y. Hong, and L. G. Bushnell, "Stability analysis of networked control systems," Control Systems Technology, IEEE Transactions on, vol. 10, pp. 438-446, 2002.
    [77] C. Mo-Yuen and Y. Tipsuwan, "Gain adaptation of networked DC motor controllers based on QoS variations," Industrial Electronics, IEEE Transactions on, vol. 50, pp. 936-943, 2003.
    [78] L. Zhang, Y. Shi, T. Chen, and B. Huang, "A New Method for Stabilization of Networked Control Systems With Random Delays," Automatic Control, IEEE Transactions on, vol. 50, pp. 1177-1181, 2005.
    [79] L. A. Montestruque and P. Antsaklis, "Stability of model-based networked control systems with time-varying transmission times," Automatic Control, IEEE Transactions on, vol. 49, pp. 1562-1572, 2004.
    [80] Y. Dong, H. Qing-Long, and P. Chen, "State feedback controller design of networked control systems," Circuits and Systems II: Express Briefs, IEEE Transactions on, vol. 51, pp. 640-644, 2004.
    [81] O. Beldiman, G. C. Walsh, and L. Bushnell, "Predictors for networked control systems," in American Control Conference, 2000. Proceedings of the 2000, 2000, pp. 2347-2351 vol.4.
    [82] W. Aiguo, W. Dongqing, and L. Jin, "Application of generalized predictive control with neural network error correction in networked control system," in Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on, 2004, pp. 1386-1390 Vol.2.
    [83] M. Dejun, F. Lei, and D. Guanzhong, "Research on Generalized Predictive Control Algorithm of Networked Control System," in Control Conference, 2006. CCC 2006. Chinese, 2006, pp. 119-122.
    [84] T. Poi Loon and C. W. de Silva, "Compensation for transmission delays in an ethernet-based control network using variable-horizon predictive control," Control Systems Technology, IEEE Transactions on, vol. 14, pp. 707-718, 2006.
    [85] E. Witrant, P. Pan Gun, M. Johansson, C. Fischione, and K. H. Johansson, "Predictive control over wireless multi-hop networks," in Control Applications, 2007. CCA 2007. IEEE International Conference on, 2007, pp. 1037-1042.
    [86] Z.-P. Jiang, E. Lefeber, and H. Nijmeijer, "Saturated stabilization and tracking of a nonholonomic mobile robot," Systems & Control Letters, vol. 42, pp. 327-332, 4/23/ 2001.
    [87] J. Jakubiak, E. Lefeber, K. Tchoń, and H. Nijmeijer, "Two observer-based tracking algorithms for a unicycle mobile robot," International Journal of Applied Mathematics and Computer Science, vol. 12, p. 513, 2002.
    [88] D. W. Clarke, C. Mohtadi, and P. S. Tuffs, "Generalized Predictive Control - Part I. The Basic Algorithm," Automatica, vol. 23, pp. 137-148, 1987.
    [89] C. B. E.F.Camacho, Model predictive Control: Springer, 2004.
    [90] D. W. Clarke, C. Mohtadi, and P. S. Tuffs, "Generalized Predictive Control - Part II. Extensions and Interpretations " Automatica, vol. 23, pp. 149-160, 1987.
    [91] J. Shi, A. G. Kelkar, and D. Soloway, "GPC-based stable reconfigurable control," in 2003 ASME International Mechanical Engineering Congress, Washington, DC., 2003, pp. 821-828.
    [92] K. Belda and J. Bohm, "Range-space predictive control for optimal robot motion," INTERNATION JOURNAL OF CIRCUITS, SYSTEMS and SIGNAL PROCESSING, vol. Issue 1, Vol.1, 2007.
    [93] W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes: The Art of Scientific Computing, 3rd ed.: Cambridge Univ Pr, 2007.
    [94] G. H. Golub and C. F. V. Loan, Matrix Computations, Third ed.: The Johns Hopkings University, 1996.
    [95] W. Y. Yang, W. Cao, T.-S. Chung, and J. Morris, Applied Numerical Methods Using MATLAB: John Wiley & Sons, Inc., Hoboken, New Jersey., 2005.
    [96] D. Soloway, J. Shi, and A. Kelkar, "GPC-Based Stable Reconfigurable Control," NASA Ames Research Center.

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