Distributed adaptive optimization-based formation tracking with double parameter projections for multi-agent systems |
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| Institution: | 1. School of Transportation Science and Engineering, Beihang University, Beijing 100083, PR China;2. Department of Mathematics, Beijing Jiaotong University, Beijing 100044, PR China;3. Texas A & M University at Qatar, Doha 23874, Qatar;1. Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, School of Energy and Environment, Southeast University, Nanjing 210096, China;2. Department of Electrical and Computer Engineering, Baylor University, Waco, TX 76798-7356, USA;1. College of Automation Engineering, Nanjing Univ. of Aeronautics and Astronautics, Nanjing 210016, China;2. Key Laboratory of Navigation, Control and Health-Management Technologies of Advanced Aerocraft (Nanjing Univ. of Aeronautics and Astronautics), Ministry of Industry and Information Technology, Nanjing, China;1. School of Aerospace Science and Technology, Xidian University, Xi’an 710071, PR China;2. School of Mathematics and Statistics, Tianshui Normal University, Tianshui 741001, PR China |
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| Abstract: | In this paper, a distributed adaptive optimization-based formation tracking strategy with double parameter projections for multi-agent systems is addressed under a centralized task allocation and distributed task execution (CTA-DTE) framework. Since a pre-described formation strategy is unable to adapt to a complex and dynamic environment, an optimization-based approach is proposed to transfer the formation tracking problem into a time-varying optimization one, subject to some constraints with several time-varying parameters which determine the rule of formation configuration change adaptively. These parameters are computed by a centralized unit and allocated to each agent as a global mission. Furthermore, each agent cooperates with others to execute this mission under a distributed optimization-based strategy, which combines a geometric center observer technology and a novel double parameter projections technology. The former ensures accurate tracking of a continuous reference trajectory. The latter guarantees that all agents enter into a time-varying security region and never escape from it, and meanwhile, all agents are attracted towards the best time-varying formation configuration via a gradient descent with a compensation. Finally, some simulation results are illustrated to verify the effectiveness of the strategy. |
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