Neural-Adaptive Finite-Time Formation Tracking Control of Multiple Nonholonomic Agents With a Time-Varying Target
| Autor: | Bing-Liang Hu, Chang-Duo Liang, Xiao-Kang Wu, Ming-Feng Ge, Kai-Bo Zhou |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Nonholonomic system
Lyapunov stability 0209 industrial biotechnology General Computer Science Artificial neural network leader-following formation tracking problem (FTP) Computer science General Engineering 02 engineering and technology Kinematics Multiple nonholonomic agent system (MNAS) distributed controller-estimator algorithm (DCEA) 020901 industrial engineering & automation Robustness (computer science) Control theory 0202 electrical engineering electronic engineering information engineering radial basis function (RBF) neural network 020201 artificial intelligence & image processing General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Finite time lcsh:TK1-9971 Parametric statistics |
| Zdroj: | IEEE Access, Vol 8, Pp 62943-62953 (2020) |
| ISSN: | 2169-3536 |
| Popis: | This paper investigates the leader-following formation tracking problem (FTP) for multiple nonholonomic agent systems (MNASs) in the presence of external disturbances and parametric uncertainties, where both the kinematics and dynamics of the agents are taken into consideration. A novel finite-time distributed controller-estimator algorithm (DCEA) is designed to handle such a challenging problem. Based on Lyapunov stability method, the sufficient conditions for finite-time stability of the closed-loop system are derived. Finally, the simulation results are presented to demonstrate the effectiveness and the robustness of the proposed DCEA. |
| Databáze: | OpenAIRE |
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