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Variable gain design in stochastic iterative learning control

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Variable gain design in stochastic iterative learning control/ by Dong Shen.
作者:	Shen, Dong.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	xi, 350 p. :ill. (chiefly color), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Industrial Automation. -
電子資源:	https://doi.org/10.1007/978-981-97-8281-9
ISBN:	9789819782819

Variable gain design in stochastic iterative learning control
Shen, Dong.

Variable gain design in stochastic iterative learning control[electronic resource] /by Dong Shen. - Singapore :Springer Nature Singapore :2024. - xi, 350 p. :ill. (chiefly color), digital ;24 cm. - Intelligent control and learning systems,v. 132662-5466 ;. - Intelligent control and learning systems ;v. 11..

Introduction -- Preliminary Results -- Decreasing Gain Design -- Adaptive Gain Design -- Event triggering Gain Design -- Optimal Gain Design -- Conclusions and Open Problems -- References.

This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control.

ISBN: 9789819782819

Standard No.: 10.1007/978-981-97-8281-9doiSubjects--Topical Terms:

1388732
Industrial Automation.

LC Class. No.: TJ217.5

Dewey Class. No.: 629.8

Variable gain design in stochastic iterative learning control
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