Intelligent Adaptive Control for a Pneumatic Servo System

Autor:	Yuuji Yamada
Rok vydání:	2003
Předmět:	Engineering Adaptive control Artificial neural network business.industry Process (computing) Control engineering General Medicine Servomechanism law.invention Control theory law Control system Minimum phase business Intelligent control
Zdroj:	TRANSACTIONS OF THE JAPAN FLUID POWER SYSTEM SOCIETY. 34:1-7
ISSN:	1349-7022 1880-3121
Popis:	In this paper, we propose a design scheme for the intelligent control for a pneumatic servo system. In this design scheme, the unknown parameters are identified first and then the plant model is determined whether to be minimum-phase or not, because the discrete-time plant model of the pneumatic servo system becomes a minimum phase or a non-minimum phase depending on the difference in the sampling period and the load mass. Next a model reference adaptive control system (MRACS) is adopted in the case of minimum-phase and an adaptive pole-assignment control system (APACS) is used in the other case. Furthermore, in this design scheme, neural networks (NN) in the adaptive controller and a deference process of the signals in the identification mechanism are introduced to eliminate the influence of non-linear elements caused by compressibility of the air and various frictions. The effectiveness of the proposed design scheme is confirmed by experiments using an existing pneumatic servo system.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ac0ee81cf65ff15a819ec316b1cb9543 https://doi.org/10.5739/jfps.34.1 Zobrazit plný text záznamu