Decentralized multi-agent formation control with pole-region placement via cone-complementarity linearization

• Autorzy: González Antonio , Sala Antonio , Armesto Leopoldo

Identyfikatory

DOI

10.34768/amcs-2022-0030

• Języki publikacji: EN

Abstrakty

EN

An output-feedback decentralised formation control strategy is pursued under pole-region constraints, assuming that the agents have access to relative position measurements with respect to a set of neighbors in a graph describing the sensing topology. No communication between the agents is assumed; however, a shared one-way communication channel with a pilot is needed for steering tasks. Each agent has a separate copy of the same controller. A virtual structure approach is presented for the formation steering as a whole; actual formation control is established via cone-complementarity linearization algorithms for the appropriate matrix inequalities. In contrast to other research where only stable consensus is pursued, the proposed method allows us to specify settling-time, damping and bandwidth limitations via pole regions. In addition, a full methodology for the decoupled handling of steering and formation control is provided. Simulation results in the example section illustrate the approach.

Słowa kluczowe

EN

multiagent autonomous system; formation control; linear matrix inequalities; cone complementarity linearization

PL

system wieloagentowy; sterowanie formacją; liniowe nierówności macierzowe

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2022
• Tom: Vol. 32, no. 3
• Strony: 415--428
• Opis fizyczny: Bibliogr. 26 poz., rys., wykr.

Twórcy

autor

González Antonio

• University Institute of Control Systems and Industrial Computing (AI2), Polytechnic University of Valencia, Camino de Vera, s/n, 46022 València, Spain

autor

Sala Antonio

• University Institute of Control Systems and Industrial Computing (AI2), Polytechnic University of Valencia, Camino de Vera, s/n, 46022 València, Spain

autor

Armesto Leopoldo

• Design and Manufacturing Institute (IDF), Polytechnic University of Valencia, Camino de Vera, s/n, 46022 València, Spain

Bibliografia

• [1] Bai, H. and Wen, J.T. (2010). Cooperative load transport: A formation-control perspective, IEEE Transactions on Robotics 26(4): 742–750.
• [2] Bechlioulis, C.P., Giagkas, F., Karras, G.C. and Kyriakopoulos, K.J. (2019). Robust formation control for multiple underwater vehicles, Frontiers in Robotics and AI 6(2019): 90.
• [3] Dehghani, M.A. and Menhaj, M.B. (2016). Communication free leader–follower formation control of unmanned aircraft systems, Robotics and Autonomous Systems 80(2016): 69–75.
• [4] Dong, X., Yu, B., Shi, Z. and Zhong, Y. (2014). Time-varying formation control for unmanned aerial vehicles: Theories and applications, IEEE Transactions on Control Systems Technology 23(1): 340–348.
• [5] El Ghaoui, L., Oustry, F. and AitRami, M. (1997). A cone complementarity linearization algorithm for static output-feedback and related problems, IEEE Transactions on Automatic Control 42(8): 1171–1176.
• [6] Farrera, B., López-Estrada, F.-R., Chadli, M., Valencia-Palomo, G. and Gómez-Peñate, S. (2020). Distributed fault estimation of multi-agent systems using a proportional-integral observer: A leader-following application, International Journal of Applied Mathematics and Computer Science 30(3): 551–560, DOI: 10.34768/amcs-2020-0040.
• [7] González, A., Aranda, M., López-Nicolás, G. and Sagüés, C. (2019). Robust stability analysis of formation control in local frames under time-varying delays and actuator faults, Journal of the Franklin Institute 356(2): 1131–1153.
• [8] González-Sierra, J., Dzul, A. and Martínez, E. (2022). Formation control of distance and orientation based-model of an omnidirectional robot and a quadrotor UAV, Robotics and Autonomous Systems 147(2022): 103921.
• [9] He, S., Wang, M., Dai, S.-L. and Luo, F. (2018). Leader–follower formation control of USVs with prescribed performance and collision avoidance, IEEE Transactions on Industrial Informatics 15(1): 572–581.
• [10] Kamel, M.A. and Zhang, Y. (2015). Decentralized leader–follower formation control with obstacle avoidance of multiple unicycle mobile robots, 2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE), Halifax, Canada, pp. 406–411.
• [11] Lee, G. and Chwa, D. (2018). Decentralized behavior–based formation control of multiple robots considering obstacle avoidance, Intelligent Service Robotics 11(1): 127–138.
• [12] Li, Z., Liu, H.H., Zhu, B. and Gao, H. (2015). Robust second-order consensus tracking of multiple 3-DOF laboratory helicopters via output feedback, IEEE/ASME Transactions on Mechatronics 20(5): 2538–2549.
• [13] Oh, K.-K., Park, M.-C. and Ahn, H.-S. (2015). A survey of multi-agent formation control, Automatica 53(2015): 424–440.
• [14] Olfati-Saber, R. and Murray, R. (2004). Consensus problems in networks of agents with switching topology and time-delays, IEEE Transactions on Automatic Control 49(9): 1520–1533.
• [15] Peaucelle, D., Arzelier, D., Bachelier, O. and Bernussou, J. (2000). A new robust D-stability condition for real convex polytopic uncertainty, Systems and Control Letters 40(1): 21–30.
• [16] Peng, C., Zhang, A. and Li, J. (2021). Neuro-adaptive cooperative control for high-order nonlinear multi-agent systems with uncertainties, International Journal of Applied Mathematics and Computer Science 31(4): 635–645, DOI: 10.34768/amcs-2021-0044.
• [17] Rahimi, R., Abdollahi, F. and Naqshi, K. (2014). Time-varying formation control of a collaborative heterogeneous multi agent system, Robotics and Autonomous Systems 62(12): 1799–1805.
• [18] Ren, W. and Atkins, E. (2005). Second-order consensus protocols in multiple vehicle systems with local interactions, AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco, USA, p. 6238.
• [19] Ren, W. and Beard, R.W. (2004). Decentralized scheme for spacecraft formation flying via the virtual structure approach, Journal of Guidance, Control, and Dynamics 27(1): 73–82.
• [20] Ren, W. and Beard, R.W. (2008). Distributed Consensus in Multi-Vehicle Cooperative Control, Springer, London.
• [21] Ren, W. and Sorensen, N. (2008). Distributed coordination architecture for multi-robot formation control, Robotics and Autonomous Systems 56(4): 324–333.
• [22] Tian, B., Lu, H., Zuo, Z. and Yang, W. (2018). Fixed-time leader–follower output feedback consensus for second-order multiagent systems, IEEE Transactions on Cybernetics 49(4): 1545–1550.
• [23] Wen, C., Liu, F., Song, Q. and Feng, X. (2016). Observer-based consensus of second-order multi-agent systems without velocity measurements, Neurocomputing 179(2016): 298–306.
• [24] Zhai, G., Okuno, S., Imae, J. and Kobayashi, T. (2009). A matrix inequality based design method for consensus problems in multi-agent systems, International Journal of Applied Mathematics and Computer Science 19(4): 639–646, DOI: 10.2478/v10006-009-0051-1.
• [25] Zhang, H. and Chen, J. (2017). Bipartite consensus of multi-agent systems over signed graphs: State feedback and output feedback control approaches, International Journal of Robust and Nonlinear Control 27(1): 3–14.
• [26] Zou, Y., Zhou, Z., Dong, X. and Meng, Z. (2018). Distributed formation control for multiple vertical take off and landing UAVs with switching topologies, IEEE/ASME Transactionson Mechatronics 23(4): 1750–1761.

Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023)