Neuro-Fuzzy Controller for a XY Positioning Table

Autor:	Jun Oh Jang, Pyeong Gi Lee, Gi Joon Jeon, Young Deuk Moon, Hee Tae Chung
Rok vydání:	2007
Předmět:	Tracking error Computational Theory and Mathematics Artificial Intelligence Computer science Control theory Control system IBM PC compatible Bounded function Tracking (particle physics) Error detection and correction Software Inner loop Theoretical Computer Science
Zdroj:	Intelligent Automation & Soft Computing. 13:153-169
ISSN:	2326-005X 1079-8587
DOI:	10.1080/10798587.2007.10642957
Popis:	This paper presents control designs using an neuro-fuzzy network. (NFN) for il XY positioning table. The neuro-furzy controller is composed of an outer PD tracking loop for stabilization of the fast flexible mode dynamics and an NFN inner loop used to compensate for the system nonlinearities. A tuning algorithm is given for the NFN parameters so that the NFN control scheme becomes adaptive, guaranteeing small tracking errors and bounded weight estimates. Formal nonlinear stability proofs are given to show that the tracking error is small. The proposed new-fuzzy controller is implemented and texted on an IBM PC-based XY positioning table, and is applicable to many precision XY tables. The algorithm, simulation, and experimental results we described. The experimental results are shown to be superior to those of conventional control.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::12441810cb10fed3a200f54a47982e62 https://doi.org/10.1080/10798587.2007.10642957 Zobrazit plný text záznamu