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Distributed model reference control for synchronization of a vehicle platoon with limited output information and subject to periodical intermittent information

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Vehicles involved in platoon formation may experience difficulties in obtaining full-state information that can be exchanged and used for controller synthesis. Therefore, a distributed controller based on a model reference and designed utilizing a cooperative observer is proposed for vehicle platoon synchronization. The proposed controller is composed of three main blocks, namely, the reference model, the cooperative observer and the main controller. The reference model is developed by using a homogeneous vehicle platoon that utilizes cooperative full-state information. The cooperative observer is a state estimator which is constructed based on the cooperative output estimation error. It provides state estimates to be used by the main controller. The main controller is constructed from a nominal control and a synchronization input. The nominal control has the main task of tracking the lead vehicle, while in order to reduce the synchronization error, the synchronization input is added by utilizing the cooperative disagreement error. Stability analysis is focused on the vehicle platoon when it is subjected to completely periodical intermittent information. The condition on the information rate is derived for guaranteeing the synchronization of the platoon. Numerical simulation of a vehicle platoon consisting of one leader and five followers is used to examine the performance of the controller.
Rocznik
Strony
537--551
Opis fizyczny
Bibliogr. 36 poz., rys., tab., wykr.
Twórcy
  • Department of Electrical Engineering, University of Surabaya, Raya Kalirungkut 60293, Surabaya, East Java, Indonesia
  • Department of Electrical Engineering, University of Surabaya, Raya Kalirungkut 60293, Surabaya, East Java, Indonesia
  • School of Information, Computer, and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, 131 Moo 5, Tiwanon Road, Bangkadi, Muang, Pathum Thani 12000, Thailand
Bibliografia
  • [1] Abou Harfouch, Y., Yuan, S. and Baldi, S. (2017). An adaptive switched control approach to heterogeneous platooning with intervehicle communication losses, IEEE Transactions on Control of Network Systems 5(3): 1434-1444, DOI: 10.1109/TCNS.2017.2718359.
  • [2] Besselink, B. and Johansson, K.H. (2017). String stability and a delay-based spacing policy for vehicle platoons subject to disturbances, IEEE Transactions on Automatic Control 62(9): 4376-4391, DOI: 10.1109/TAC.2017.2682421.
  • [3] Cavazza, B.H., Gandia, R.M., Antonialli, F., Zambalde, A.L., Nicolaï, I., Sugano, J.Y. and Neto, A. D.M. (2019). Management and business of autonomous vehicles: A systematic integrative bibliographic review, International Journal of Automotive Technology and Management 19(1-2): 31-54, DOI: 10.1504/IJATM.2019.098509.
  • [4] Chang, B.-J., Hwang, R.-H., Tsai, Y.-L., Yu, B.-H. and Liang, Y.-H. (2019). Cooperative adaptive driving for platooning autonomous self driving based on edge computing, International Journal of Applied Mathematics and Computer Science 29(2): 213-225, DOI: 10.2478/amcs-2019-0016.
  • [5] Di Bernardo, M., Salvi, A. and Santini, S. (2014). Distributed consensus strategy for platooning of vehicles in the presence of time-varying heterogeneous communication delays, IEEE Transactions on Intelligent Transportation Systems 16(1): 102-112, DOI: 10.1109/TITS.2014.2328439.
  • [6] Franzè, G., Lucia, W. and Tedesco, F. (2018). A distributed model predictive control scheme for leader-follower multi-agent systems, International Journal of Control 91(2): 369-382, DOI: 10.1080/00207179.2017.1282178.
  • [7] Hamdi, H., Rodrigues, M., Rabaoui, B. and Braiek, N.B. (2021). A fault estimation and fault-tolerant control based sliding mode observer for LPV descriptor systems with time delay, International Journal of Applied Mathematics and Computer Science 31(2): 247-258, DOI: 10.34768/amcs-2021-0017.
  • [8] Hu, J., Bhowmick, P., Arvin, F., Lanzon, A. and Lennox, B. (2020). Cooperative control of heterogeneous connected vehicle platoons: An adaptive leader-following approach, IEEE Robotics and Automation Letters 5(2): 977-984, DOI: 10.1109/LRA.2020.2966412.
  • [9] Huang, N., Duan, Z. and Zhao, Y. (2014). Leader-following consensus of second-order non-linear multi-agent systems with directed intermittent communication, IET Control Theory & Applications 8(10): 782-795, DOI: 10.1049/iet-cta.2013.0565.
  • [10] Huang, N., Duan, Z. and Zhao, Y. (2015). Consensus of multi-agent systems via delayed and intermittent communications, IET Control Theory & Applications 9(1): 62-73, DOI: 10.1049/iet-cta.2014.0729.
  • [11] Jiang, Y., Zhang, Y. and Wang, S. (2018). Distributed leader-following consensus control based optimal design for multi-agent systems with intermittent communications, 2018 Chinese Control and Decision Conference (CCDC), Shenyang, China, pp. 5341-5345, DOI: 10.1109/CCDC.2018.8408060.
  • [12] Jond, H.B. and Yıldız, A. (2022). Connected and automated vehicle platoon formation control via differential games, IET Intelligent Transport Systems 17(2): 312-326, DOI: 10.1049/itr2.12260.
  • [13] Kukurowski, N., Mrugalski, M., Pazera, M. and Witczak, M. (2022). Fault-tolerant tracking control for a non-linear twin-rotor system under ellipsoidal bounding, International Journal of Applied Mathematics and Computer Science 32(2): 171-183, DOI: 10.34768/amcs-2022-0013.
  • [14] Lewis, F.L., Zhang, H., Hengster-Movric, K. and Das, A. (2013). Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches, Springer Science, London, DOI: 10.1007/978-1-4471-5574-4.
  • [15] Li, S.E., Zheng, Y., Li, K., Wu, Y., Hedrick, J.K., Gao, F. and Zhang, H. (2017). Dynamical modeling and distributed control of connected and automated vehicles: Challenges and opportunities, IEEE Intelligent Transportation Systems Magazine 9(3): 46-58, DOI: 10.1109/MITS.2017.2709781.
  • [16] Liu, Y., Xie, D. and Shi, L. (2020). Consensus of general linear multi-agent systems with intermittent communications, International Journal of Systems Science 51(12): 2293-2305, DOI: 10.1080/00207721.2020.1793236.
  • [17] Long, X., Yu, S., Wang, Y. and Jin, L. (2014). Leader-follower consensus of multi-agent system with external disturbance based on integral sliding mode control, Proceedings of the 33rd Chinese Control Conference, Nanjing, China, pp. 1740-1745, DOI: 10.1109/ChiCC.2014.6896891.
  • [18] Ozkan, M.F. and Ma, Y. (2021). Fuel-economical distributed model predictive control for heavy-duty truck platoon, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), Indianapolis, USA, pp. 1919-1926.
  • [19] Prayitno, A. and Nilkhamhang, I. (2021). Distributed model reference adaptive control for vehicle platoons with uncertain dynamics, Engineering Journal 25(8): 173-185, DOI: 10.4186/ej.2021.25.8.173.
  • [20] Prayitno, A. and Nilkhamhang, I. (2022). Distributed model reference control for cooperative tracking of vehicle platoons subjected to external disturbances and bounded leader input, International Journal of Control, Automation and Systems 20(6): 2067-2080, DOI: 10.1007/s12555-021-0171-4.
  • [21] Qu, Z. (2009). Cooperative Control of Dynamical Systems: Applications to Autonomous Vehicles, Springer, London, DOI: 10.1007/978-1-84882-325-9.
  • [22] Song, K., Liu, F., Wang, C., Wang, P. and Min, G. (2020). Driving stability analysis using naturalistic driving data with random matrix theory, IEEE Access 8: 175521-175534.
  • [23] Wang, F., Liu, Z. and Chen, Z. (2019). Leader-following consensus of second-order nonlinear multi-agent systems with intermittent position measurements, Science China Information Sciences 62(10): 1-16, DOI: 10.1007/s11432-018-9732-7.
  • [24] Wang, Z., Wu, G. and Barth, M.J. (2017). Developing a distributed consensus-based cooperative adaptive cruise control system for heterogeneous vehicles with predecessor following topology, Journal of Advanced Transportation 2017: 1-16, DOI: 10.1155/2017/1023654.
  • [25] Wijnbergen, P., Jeeninga, M. and Besselink, B. (2021). Nonlinear spacing policies for vehicle platoons: A geometric approach to decentralized control, Systems & Control Letters 153: 104954, DOI: 10.1016/j.sysconle.2021.104954.
  • [26] Xie, Y. and Lin, Z. (2020). Global consensus of multi-agent systems with intermittent directed communication in the presence of actuator saturation, International Journal of Robust and Nonlinear Control 30(18): 8469-8484, DOI: 10.1002/rnc.5255.
  • [27] Xu, C., Xu, H., Su, H. and Liu, C. (2020). Disturbance-observer based consensus of linear multi-agent systems with exogenous disturbance under intermittent communication, Neurocomputing 404: 26-33, DOI: 10.1016/j.neucom.2020.04.051.
  • [28] Xu, H., Zeng, W. and Xu, C. (2021). Output consensus of multi-agent systems with linear dynamics via asynchronous intermittent control, 2021 40th Chinese Control Conference (CCC), Shanghai, China, pp. 5553-5558, DOI: 10.23919/CCC52363.2021.9549806.
  • [29] Xu, Z., Zegers, F.M., Wu, B., Dixon, W. and Topcu, U. (2019). Controller synthesis for multi-agent systems with intermittent communication. a metric temporal logic approach, 2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Monticello, USA, pp. 1015-1022, DOI: 10.1109/ALLERTON.2019.8919727.
  • [30] Yan, F., Dridi, M. and El Moudni, A. (2013). An autonomous vehicle sequencing problem at intersections: A genetic algorithm approach, International Journal of Applied Mathematics and Computer Science 23(1): 183-200, DOI: 10.2478/amcs-2013-0015.
  • [31] Yan, M., Song, J., Yang, P. and Zuo, L. (2018). Neural adaptive sliding-mode control of a bidirectional vehicle platoon with velocity constraints and input saturation, Complexity 2018: 1-11, DOI: 10.1155/2018/1696851.
  • [32] Zhang, H. and Lewis, F.L. (2012). Adaptive cooperative tracking control of higher-order nonlinear systems with unknown dynamics, Automatica 48(7): 1432-1439, DOI: 10.1016/j.automatica.2012.05.008.
  • [33] Zhang, H., Lewis, F.L. and Das, A. (2011). Optimal design for synchronization of cooperative systems: State feedback, observer and output feedback, IEEE Transactions on Automatic Control 56(8): 1948-1952, DOI: 10.1109/TAC.2011.2139510.
  • [34] Zheng, Y., Bian, Y., Li, S. and Li, S.E. (2019). Cooperative control of heterogeneous connected vehicles with directed acyclic interactions, IEEE Intelligent Transportation Systems Magazine 13(2): 127-141, DOI: 10.1109/MITS.2018.2889654.
  • [35] Zheng, Y., Li, S.E., Li, K., Borrelli, F. and Hedrick, J.K. (2016). Distributed model predictive control for heterogeneous vehicle platoons under unidirectional topologies, IEEE Transactions on Control Systems Technology 25(3): 899-910, DOI: 10.1109/TCST.2016.2594588.
  • [36] Zheng, Y., Li, S. E., Wang, J., Cao, D. and Li, K. (2015). Stability and scalability of homogeneous vehicular platoon: Study on the influence of information flow topologies, IEEE Transactions on Intelligent Transportation Systems 17(1): 14-26, DOI: 10.1109/TITS.2015.2402153.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3b784e90-880a-4a14-a12a-f2f9b87063e6
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