Motion control of two-link flexible-joint robot, using backstepping, neural networks, and indirect method

Autor:	W. Chatlatanagulchai, Peter H. Meckl
Rok vydání:	2005
Předmět:	Variable structure control Engineering Artificial neural network Robustness (computer science) business.industry Control theory Backstepping Robot Control engineering Robust control Control (linguistics) Motion control business
Zdroj:	Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005..
DOI:	10.1109/cca.2005.1507192
Popis:	We present a state-feedback control of a two-link flexible-joint robot. The control algorithm does not require the mathematical model representing the robot. Three-layer neural networks approximate the unknown plant functions. The neural network weights are adapted on-line. We use backstepping control structure together with variable structure control to provide robustness to all uncertainties. We have included experimental results to show the effectiveness of the control algorithm
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d6e650227725a876ce077ca13d47c5b8 https://doi.org/10.1109/cca.2005.1507192 Zobrazit plný text záznamu