M. R. Rahimi Khoygani, R. Ghasemi, P. Ghayoomi. Robust Observer-based Control of Nonlinear Multi-omnidirectional Wheeled Robot Systems via High Order Sliding-mode Consensus Protocol. International Journal of Automation and Computing, vol. 18, no. 5, pp.787-801, 2021. https://doi.org/10.1007/s11633-020-1254-z
Citation: M. R. Rahimi Khoygani, R. Ghasemi, P. Ghayoomi. Robust Observer-based Control of Nonlinear Multi-omnidirectional Wheeled Robot Systems via High Order Sliding-mode Consensus Protocol. International Journal of Automation and Computing, vol. 18, no. 5, pp.787-801, 2021. https://doi.org/10.1007/s11633-020-1254-z

Robust Observer-based Control of Nonlinear Multi-omnidirectional Wheeled Robot Systems via High Order Sliding-mode Consensus Protocol

doi: 10.1007/s11633-020-1254-z
More Information
  • Author Bio:

    M. R. Rahimi Khoygani received the B. Sc. degree in electrical power engineering from the Islamic Azad University (IAU), Iran in 2012, the M. Sc. degree in control engineering from IAU, Iran in 2015. He is currently a member of Department of Control Engineering, Qom University, Iran.His research interests include neural net, fuzzy systems, intelligent systems, robotics, control of nonlinear systems, nonlinear observer, intelligent state estimation, and adaptive control.E-mail: mrrahimikh@gmail.com (Corresponding author)ORCID iD: 0000-0002-0231-7701

    R. Ghasemi received the B. Sc. degree in electrical engineering from Semnan University, Iran in 2000, and the M. Sc. and Ph. D. degrees in control engineering from Amirkabir University of Technology, Iran in 2004 and 2009, respectively. He joined Department of Electrical Engineering, Qom University, Iran, where he is currently a professor of electrical engineering.His research interests include large-scale systems, adaptive control, robust control, nonlinear control, and intelligent systems.E-mail: r.ghasemi@qom.ac.ir

    P. Ghayoomi received the B. Sc. and M. Sc. degrees in control engineering from Islamic Azad University, Iran in 2013 and 2016, respectively. He is currently a member of Department of Control Engineering, Qom University, Iran. His research interests include intelligent systems, robotics, nonlinear observer, and adaptive control. E-mail: pooriyaghayoomi@gmail.com

  • Received Date: 2020-03-05
  • Accepted Date: 2020-09-08
  • Available Online: 2021-09-08
  • Publish Date: 2021-10-01
  • This paper presents a novel observer-based controller for a class of nonlinear multi-agent robot models using the high order sliding mode consensus protocol. In many applications, demand for autonomous vehicles is growing; omnidirectional wheeled robots are suggested to meet this demand. They are flexible, fast, and autonomous, able to find the best direction and can move on an optional path at any time. Multi-agent omnidirectional wheeled robot (MOWR) systems consist of several similar or different robots and there are multiple different interactions between their agents, thus the MOWR systems have complex dynamics. Hence, designing a robust reliable controller for the nonlinear MOWR operations is considered an important obstacles in the science of the control design. A high order sliding mode is selected in this work that is a suitable technique for implementing a robust controller for nonlinear complex dynamics models. Furthermore, the proposed method ensures all signals involved in the multi-agent system (MAS) are uniformly ultimately bounded and the system is robust against the external disturbances and uncertainties. Theoretical analysis of candidate Lyapunov functions has been presented to depict the stability of the overall MAS, the convergence of observer and tracking error to zero, and the reduction of the chattering phenomena. In order to illustrate the promising performance of the methodology, the observer is applied to two nonlinear dynamic omnidirectional wheeled robots. The results display the meritorious performance of the scheme.

     

  • loading
  • [1]
    M. R. R. Khoygani, R. Ghasemi, A. R. Vali. Intelligent nonlinear observer design for a class of nonlinear discrete-time flexible joint robot. Intelligent Service Robotics, vol. 8, no. 1, pp. 45–56, 2015. DOI: 10.1007/s11370-014-0162-x.
    [2]
    S. R. Sahoo, S. S. Chiddarwar. Flatness-based control scheme for hardware-in-the-loop simulations of omnidirectional mobile robot. Simulation, vol. 96, no. 2, pp. 169–183, 2020. DOI: 10.1177/0037549719859064.
    [3]
    V. Alakshendra, S. S. Chiddarwar. Adaptive robust control of Mecanum-wheeled mobile robot with uncertainties. Nonlinear Dynamics, vol. 87, no. 4, pp. 2147–2169, 2017. DOI: 10.1007/s11071-016-3179-1.
    [4]
    V. Alakshendra, S. S. Chiddarwar. Simultaneous balancing and trajectory tracking control for an omnidirectional mobile robot with a cylinder using switching between two robust controllers. International Journal of Advanced Robotic Systems, vol. 14, no. 6, pp. 1–16, 2017. DOI: 10.1177/1729881417738728.
    [5]
    B. E. Byambasuren, D. Kim, M. Oyun-Erdene, C. Bold, J. Yura. Inspection robot based mobile sensing and power line tracking for smart grid. Sensors, vol. 16, no. 2, Article number 250, 2016. DOI: 10.3390/s16020250.
    [6]
    J. M. Bengochea-Guevara, J. Conesa-Munoz, D. Andujar, A. Ribeiro. Merge fuzzy visual servoing and GPS-based planning to obtain a proper navigation behavior for a small crop-inspection robot. Sensors, vol. 16, no. 3, Article number 276, 2016. DOI: 10.3390/s16030276.
    [7]
    J. G. Blitch. Artificial intelligence technologies for robot assisted urban search and rescue. Expert Systems with Applications, vol. 11, no. 2, pp. 109–124, 1996. DOI: 10.1016/0957-4174(96)00038-3.
    [8]
    S. Fish. UGVs in future combat systems. In Proceedings of SPIE 5422, Unmanned Ground Vehicle Technology VI, Defense and Security, SPIE, Orlando, USA, pp. 288–291, 2004.
    [9]
    J. Lafaye, D. Gouaillier, P. B. Wieber. Linear model predictive control of the locomotion of Pepper, a humanoid robot with omnidirectional wheels. In Proceedings of IEEE-RAS International Conference on Humanoid Robots, IEEE, Madrid, Spain, pp. 336–341, 2014.
    [10]
    M. Wada, H. H. Asada. Design and control of a variable footprint mechanism for holonomic omnidirectional vehicles and its application to wheelchairs. IEEE Transactions on Robotics and Automation, vol. 15, no. 6, pp. 978–989, 1999. DOI: 10.1109/70.817663.
    [11]
    United Nations. World Population Ageing 2013, [Online], Available: https://www.un.org/en/development/desa/population/publications/pdf/ageing/WorldPopulationAgeing2013.pdf, December 15, 2015.
    [12]
    World Health Organization. World Report on Ageing and Health, [Online], Available: http://apps.who.int/iris/bitstream/10665/186463/1/9789240694811-eng.pdf, February 18, 2016.
    [13]
    C. Moron, A. Payan, A. Garcia, F. Bosquet. Domotics project housing block. Sensors, vol. 16, no. 5, Article number 741, 2016. DOI: 10.3390/s16050741.
    [14]
    E. Clotet, D. Martinez, J. Moreno, M. Tresanchez, J. Palacin. Assistant Personal Robot (APR): Conception and application of a Tele-operated assisted living robot. Sensors, vol. 16, no. 5, Article number 610, 2016. DOI: 10.3390/s16050610.
    [15]
    M. Tavakoli, J. Lourenco, C. Viegas, P. Neto, A. T. De Almeida. The hybrid OmniClimber robot: Wheel based climbing, arm based plane transition, and switchable magnet adhesion. Mechatronics, vol. 36, pp. 136–146, 2016. DOI: 10.1016/j.mechatronics.2016.03.007.
    [16]
    J. Santos, A. Conceicao, T. Santos, H. Araujo. Remote control of an omnidirectional mobile robot with time-varying delay and noise attenuation. Mechatronics, vol. 52, pp. 7–21, 2018. DOI: 10.1016/j.mechatronics.2018.04.003.
    [17]
    D. B. Zhao, J. Q. Yi. Introduction to Omni-directional Mobile Robot, Beijing, China: Science Press, 2010. (in Chinese)
    [18]
    X. Y. Deng, J. Q. Yi, D. B. Zhao. Kinematic analysis of an omni-directional mobile robot. Robot, vol. 26, no. 1, pp. 49–53, 2004. DOI: 10.3321/j.issn:1002-0446.2004.01.011. (in Chinese)
    [19]
    C. Ren, S. G. Ma. Trajectory tracking control of an omnidirectional mobile robot with friction compensation. In Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Daejeon, South Korea, pp. 5361–5366, 2016.
    [20]
    H. P. Oliveira, A. J. Sousa, A. P. Moreira, P. J. Costa. Dynamical models for omni-directional robots with 3 and 4 wheels. In Proceedings of the 5th International Conference on Informatics in Control, Automation and Robotics, INSTICC Press, Madeira, Portugal, pp. 189–196, 2008.
    [21]
    C. Sprunk, B. Lau, P. Pfaff, W. Burgard. An accurate and efficient navigation system for omnidirectional robots in industrial environments. Autonomous Robots, vol. 41, no. 2, pp. 473–493, 2017. DOI: 10.1007/s10514-016-9557-1.
    [22]
    D. S. Lal, A. Vivek. Dynamic modeling and control of omni-directional mobile robots. In Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, IEEE, Kollam, India, pp. 1–7, 2017.
    [23]
    T. F. Wu, H. C. Huang, P. S. Tsai, N. T. Hu, Z. Q. Yang. The tracking control design of adaptive fuzzy CMAC for an omni-directional mobile robot. Journal of Computers, vol. 28, no. 1, pp. 247–260, 2017. DOI: 10.3966/199115592017022801019.
    [24]
    D. Xu, D. B. Zhao, J. Q. Yi, X. M. Tan. Trajectory tracking control of omnidirectional wheeled mobile manipulators: Robust neural network-based sliding mode approach. IEEE Transactions on Systems,Man,and Cybernetics Part B:Cybernetics, vol. 39, no. 3, pp. 788–799, 2009. DOI: 10.1109/TSMCB.2008.2009464.
    [25]
    C. C. Tsai, H. L.Wu, F. C. Tai, Y. S. Chen. Distributed consensus formation control with collision and obstacle avoidance for uncertain networked omnidirectional multi-robot systems using fuzzy wavelet neural networks. International Journal of Fuzzy Systems, vol. 19, no. 5, pp. 1375–1391, 2017. DOI: 10.1007/s40815-016-0239-0.
    [26]
    M. Fatima, H. Assia, H. Habib. Adaptive nonlinear control of a synchronous generator. Carpathian Journal of Electronic and Computer Engineering, vol. 11, no. 2, pp. 39–43, 2018. DOI: 10.2478/cjece-2018-0017.
    [27]
    M. P. Aghababa. Robust stabilization and synchronization of a class of fractional-order chaotic systems via a novel fractional sliding mode controller. Communications in Nonlinear Science and Numerical Simulation, vol. 17, no. 6, pp. 2670–2681, 2012. DOI: 10.1016/j.cnsns.2011.10.028.
    [28]
    K. Shojaei, A. M. Shahri. Adaptive robust time-varying control of uncertain non-holonomic robotic systems. IET Control Theory &Applications, vol. 6, no. 1, pp. 90–102, 2012. DOI: 10.1049/iet-cta.2010.0655.
    [29]
    S. T. Kao, W. J. Chiou, M. T. Ho. Integral sliding mode control for trajectory tracking control of an omnidirectional mobile robot. In Proceedings of the 8th Asian Control Conference, IEEE, Kaohsiung, China, pp. 765–770, 2011.
    [30]
    S. V. Drakunov, V. I. Utkin. Sliding mode control in dynamic systems. International Journal of Control, vol. 55, no. 4, pp. 1029–1037, 1992. DOI: 10.1080/00207179208934270.
    [31]
    L. Long, D. B. Ren, J. Y. Zhang. Terminal sliding mode control for vehicle longitudinal following in automated highway system. In Proceedings of the 27th Chinese Control Conference, IEEE, Kunming, China, pp. 605–608, 2008.
    [32]
    Y. H. Chang, C. W. Chang, W. C. Chan. Fuzzy sliding-mode consensus control for multi-agent systems. In Proceedings of American Control Conference, IEEE, San Francisco, USA, pp. 1636–1641, 2011.
    [33]
    C. W. Chang, C. L. Chen, Y. H. Chang, C. W. Tao. Adaptive fuzzy sliding-mode formation control for second-order multi-agent systems. In Proceedings of International Conference on System Science and Engineering, IEEE, Taipei, China, pp. 310–314, 2010.
    [34]
    S. Muhammad, M. Idrees. Comparative study of hierarchical sliding mode control and decoupled sliding mode control. In Proceedings of the 12th IEEE Conference on Industrial Electronics and Applications, IEEE, Siem Reap, Cambodia, pp. 818–824, 2017.
    [35]
    S. Alvarez-Rodriguez, G. Flores, N. A. Ochoa. Variable gains sliding mode control. International Journal of Control,Automation and Systems, vol. 17, no. 3, pp. 555–564, 2019. DOI: 10.1007/s12555-018-0095-9.
    [36]
    N. Zhao, J. D. Zhu. Sliding mode control for robust consensus of linear multi-agent systems. In Proceedings of the 10th World Congress on Intelligent Control and Automation, IEEE, Beijing, China, pp. 1378–1382, 2012.
    [37]
    M. R. James, J. S. Baras. An observer design for nonlinear control systems. Analysis and Optimization of Systems, A. Bensoussan, J. L. Lions, Eds., Berlin Heidelberg, Germany: Springer, pp. 170–180, 1988.
    [38]
    V. Gazi, B. Fidan. Coordination and control of multi-agent dynamic systems: Models and approaches. Swarm Robotics, E. Sahin, W. M. Spears, A. F. T. Winfield, Eds., Berlin Heidelberg, Germany: Springer, pp. 71–102, 2007.
    [39]
    X. J. Long, S. H. Yu, Y. L. Wang, L. N. Jin. Leader-follower consensus of multi-agent system with external disturbance based on integral sliding mode control. In Proceedings of the 33rd Chinese Control Conference, IEEE, Nanjing, China, pp. 1740–1745, 2014.
    [40]
    U. B. Kamble, J. O. Chandle, V. S. Lahire, R. D. Langde. Second order twisting sliding mode control of multi-agent network with input disturbance. In Proceedings of Fourth International Conference on Computing, Communications and Networking Technologies, IEEE, Tiruchengode, India, 2013.
    [41]
    C. E. Ren, C. L. P. Chen. Sliding mode leader-following consensus controllers for second-order non-linear multi-agent systems. IET Control Theory &Applications, vol. 9, no. 10, pp. 1544–1552, 2015. DOI: 10.1049/iet-cta.2014.0523.
    [42]
    H. K. Khalil. Nonlinear Systems, 3rd ed., New York, USA: Prentice-Hall, 2001.
    [43]
    M. Panda, B. Das, B. Subudhi, B. B. Pati. A comprehensive review of path planning algorithms for autonomous underwater vehicles. International Journal of Automation and Computing, vol. 17, no. 3, pp. 321–352, 2020. DOI: 10.1007/s11633-019-1204-9.
    [44]
    N. Hacene, B. Mendil. Fuzzy behavior-based control of three wheeled omnidirectional mobile robot. International Journal of Automation and Computing, vol. 16, no. 2, pp. 163–185, 2019. DOI: 10.1007/s11633-018-1135-x.
    [45]
    A. Kumar, A. Ojha. Experimental evaluation of certain pursuit and evasion schemes for wheeled mobile robots. International Journal of Automation and Computing, vol. 16, no. 4, pp. 491–510, 2019. DOI: 10.1007/s11633-018-1151-x.
    [46]
    I. Ardiyanto, J. Miura. Time-space viewpoint planning for guard robot with chance constraint. International Journal of Automation and Computing, vol. 16, no. 4, pp. 475–490, 2019. DOI: 10.1007/s11633-018-1146-7.
    [47]
    H. X. Ma, W. Zou, Z. Zhu, C. Zhang, Z. B. Kang. Selection of observation position and orientation in visual servoing with eye-in-vehicle configuration for manipulator. International Journal of Automation and Computing, vol. 16, no. 6, pp. 761–774, 2019. DOI: 10.1007/s11633-019-1181-z.
    [48]
    J. Moreno, E. Clotet, R. Lupianez, M. Tresanchez, D. Martinez, T. Palleja, J. Casanovas, J. Palacin. Design, implementation and validation of the three-wheel holonomic motion system of the assistant personal robot (APR). Sensors, vol. 16, no. 10, Article number 1658, 2016. DOI: 10.3390/s16101658.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(18)  / Tables(2)

    Article Metrics

    Article views (80) PDF downloads(18) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return