AN ADAPTIVE-CONTROL FOR CARMA SYSTEMS USING LINEAR NEURAL NETWORKS

WATANABE, K; FUKUDA, T; TZAFESTAS, SG

dc.contributor.author	WATANABE, K	en
dc.contributor.author	FUKUDA, T	en
dc.contributor.author	TZAFESTAS, SG	en
dc.date.accessioned	2014-03-01T01:08:39Z
dc.date.available	2014-03-01T01:08:39Z
dc.date.issued	1992	en
dc.identifier.issn	0020-7179	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/10629
dc.subject	Adaptive Control	en
dc.subject	Neural Network	en
dc.subject.classification	Automation & Control Systems	en
dc.title	AN ADAPTIVE-CONTROL FOR CARMA SYSTEMS USING LINEAR NEURAL NETWORKS	en
heal.type	journalArticle	en
heal.identifier.primary	10.1080/00207179208934324	en
heal.identifier.secondary	http://dx.doi.org/10.1080/00207179208934324	en
heal.language	English	en
heal.publicationDate	1992	en
heal.abstract	A neural network controller is described for controlling unknown, linear, discrete-time CARMA systems with single-input single-output. A linear two-layered neural network is used to model the inverse dynamics of the unknown plant on-line; it is learned by the delta rule, in which the difference between the actual control input to the plant, which is generated from the neural controller, and the input estimated from the inverse-dynamics model by using an actual plant output is minimized. A similar neural network is also used to estimate the unknown noise sequence so that the proposed neural network controller can treat a noisy output, where the regular dynamics are modelled on-line by using the actual plant output. Some simulation examples are finally presented to illustrate the features of the present neural controller.	en
heal.publisher	TAYLOR & FRANCIS LTD	en
heal.journalName	INTERNATIONAL JOURNAL OF CONTROL	en
dc.identifier.doi	10.1080/00207179208934324	en
dc.identifier.isi	ISI:A1992JN00400011	en
dc.identifier.volume	56	en
dc.identifier.issue	2	en
dc.identifier.spage	483	en
dc.identifier.epage	497	en