KNOWLEDGE BASED ROBOTIC CONTROL AGAINST SATURATION OF ACTUATORS OWING TO FUZZY RULES

Autor:	Jin-Zhuang Xiao, Hong-Bin Wang, Hong-Rui Wang
Rok vydání:	2008
Předmět:	Lyapunov function Robotic control Computer science Fuzzy set Fault tolerance Fuzzy logic Computer Science::Robotics symbols.namesake Knowledge extraction Artificial Intelligence Control theory symbols Robot Computer Vision and Pattern Recognition Actuator Software
Zdroj:	International Journal of Pattern Recognition and Artificial Intelligence. 22:183-194
ISSN:	1793-6381 0218-0014
DOI:	10.1142/s0218001408006107
Popis:	Considering the decreasing performance of robotic systems under the constraints of actuators, this paper concludes the rules of dynamic control process and extracts the knowledge of optimizing the output of robotic controller based on the analysis of a Lyapunov function. Then fuzzy rules are used to express the knowledge and embedded in the controller to direct the dynamic control process. Under this controller, the systemic requirement of high-level outputs of the actuators is limited to a great extent, at the same time the convergent performance is optimized by a fuzzy-sets method from which the saturated fault tolerant control is realized in robotic manipulators. Simulating results on a 2-DOF robot validate the effectiveness of the given controller.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f875038150e9918724a5edf4e0f57be1 https://doi.org/10.1142/s0218001408006107 Zobrazit plný text záznamu