Journal
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Volume 28, Issue 2, Pages 697-704Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCST.2018.2884226
Keywords
Manganese; Artificial neural networks; Collision avoidance; Multi-agent systems; Aerospace electronics; Robots; Orbits; Artificial potential function; formation tracking control; neural network (NN); relative distance constraint; tethered space net robot (TSNR)
Funding
- National Natural Science Foundation of China [61725303, 61803313, 91848205]
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In this brief, we focus on the study of formation tracking problem for a class of multiagent systems with nonlinear dynamics and external disturbances in the presence of relative distance constraints. A novel distributed formation control strategy is proposed based on an integration of radial basis function neural network (NN) with artificial potential field method. The relative distance constraints between arbitrary adjacent agents can be ensured by the artificial potential function. Based on the NN approximation property, it has been proposed to neutralize the nonlinear dynamics in agents. To account for the negative influence of the approximation error and external disturbances, a robustness term is employed. Finally, based on algebraic graph theory, matrix theory, and Barbalat's lemma, some sufficient conditions are established to accomplish the asymptotical stability of the systems for a given communication graph. The study is with application to tethered space net robot. The simulation results are performed to illustrate the performance of the proposed strategy.
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