Robust neuro‐adaptive cooperative control of multi‐agent port‐controlled Hamiltonian systems
| Autor: | Aminuddin Qureshi, Frank L. Lewis, Sami El-Ferik |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
0209 industrial biotechnology
Engineering Artificial neural network business.industry Attenuation 020208 electrical & electronic engineering Robot manipulator Control engineering 02 engineering and technology Directed graph Hamiltonian system 020901 industrial engineering & automation Control and Systems Engineering Control theory Signal Processing 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering business Hamiltonian (control theory) Parametric statistics |
| Zdroj: | International Journal of Adaptive Control and Signal Processing. 30:488-510 |
| ISSN: | 1099-1115 0890-6327 |
| DOI: | 10.1002/acs.2589 |
| Popis: | This paper presents the distributed cooperative tracking control of the multi-agent port-controlled Hamiltonian PCH systems that are networked through a directed graph. Controller is made robust against the parametric uncertainties using neural networks. Dynamics of the the proposed novel neural network tuning law is driven by both the position and the velocity errors owing to the information preserving filtering of the Hamiltonian gradient. In addition, the PCH structure of the closed-loop system is preserved and the controller achieves the disturbance attenuation objective. Simulations are performed on a group of robotic manipulators to demonstrate the efficacy of the proposed controller. Copyright © 2015 John Wiley & Sons, Ltd. |
| Databáze: | OpenAIRE |
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