Finite time formation control for multiple vehicles based on Pontryagin's minimum principle

被引:0
|
作者
Geng Z.-Y. [1 ]
机构
[1] The State Key Laboratory for Turbulence and Complex Systems, Department of Mechanics and Engineering Science, Peking University, Beijing
来源
Geng, Zhi-Yong (zygeng@pku.edu.cn) | 1600年 / Science Press卷 / 43期
基金
中国国家自然科学基金;
关键词
Consensus; Finite time formation control; Minimum principle; Multiple vehicles;
D O I
10.16383/j.aas.2017.c150537
中图分类号
学科分类号
摘要
The paper studies the problem of finite time formation control for multiple vehicles based on Pontryagin's minimum principle. The vehicle is modeled as a fully actuated rigid body with the dynamics evolving on the tangent bundle of Euclidean group. Both the formation maneuver time and the geometric structure of the formation are specified by the formation task. For the required formation, an open loop optimal control law is derived by using Pontryagin's minimum principle. In order to overcome the sensitivity of the open-loop control to the disturbance and increase the robustness of the control law to the initial perturbation, the open loop control law is converted to the closed loop form. This is done by feeding the current state back and initializing the control law at the current time, under the assumption that the mode of communication between the vehicles is all-to-all. For demonstration of the result, some numerical examples of formations for both planar and spacial vehicles are included. Copyright © 2017 Acta Automatica Sinica. All rights reserved.
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页码:40 / 59
页数:19
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  • [1] Fiorelli E., Leonard N.E., Bhatta P., Paley D.A., Bachmayer R., Frantonti D.M., Multi-AUV control and adaptive sampling in Monterey Bay, IEEE Journal of Oceanic Engineering, 31, 4, pp. 935-948, (2006)
  • [2] Alber M.S., Kiskowski A., On aggregation in CA models in biology, Journal of Physics A: Mathematical and General, 34, 48, pp. 10707-10714, (2001)
  • [3] Leonard N.E., Fiorelli E., Virtual leaders, artificial potentials and coordinated control of groups, Proceedings of the 40th IEEE Conference on Decision and Control, pp. 2968-2973, (2001)
  • [4] Jadbabaie A., Lin J., Morse A.S., Coordination of groups of mobile autonomous agents using nearest neighbor rules, IEEE Transactions on Automatic Control, 48, 6, pp. 988-1001, (2003)
  • [5] Saber R.O., Dunbar W.B., Murray R.M., Cooperative control of multi-vehicle systems using cost graphs and optimization, Proceedings of the 2003 American Control Conference, pp. 2217-2222, (2003)
  • [6] Fax J.A., Murray R.M., Information flow and cooperative control of vehicle formations, IEEE Transactions on Automatic Control, 49, 9, pp. 1465-1476, (2004)
  • [7] Sepulchre R., Paley D.A., Leonard N.E., Stabilization of planar collective motion: all-to-all communication, IEEE Transactions on Automatic Control, 52, 5, pp. 811-824, (2007)
  • [8] Scardovi L., Leonard N.E., Robustness of aggregation in networked dynamical systems, Proceedings of the 2nd International Conference on Robot Communication and Coordination, pp. 1-6, (2009)
  • [9] Chen Y.-Y., Tian Y.-P., Directed coordinated control for multi-agent formation motion on a set of given curves, Acta Automatica Sinica, 35, 12, pp. 1541-1549, (2009)
  • [10] Wang Z.X., Du D.J., Fei M.R., Average Consensus in Directed Networks of Multi-agents with Uncertain Time-varying Delays, Acta Automatica Sinica, 40, 11, pp. 2602-2608, (2014)