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A01=Dong Shen
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Variable Gain Design in Stochastic Iterative Learning Control

English

By (author): Dong Shen

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.

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A01=Dong ShenAge Group_UncategorizedAuthor_Dong Shenautomatic-updateCategory1=Non-FictionCategory=GPFCCategory=PBTCategory=PBWLCategory=TBMCategory=TJFMCOP=SingaporeDelivery_Pre-orderLanguage_EnglishPA=Not yet availablePrice_€100 and abovePS=Forthcomingsoftlaunch

Will deliver when available. Publication date 17 Dec 2024

Product Details
  • Dimensions: 155 x 235mm
  • Publication Date: 17 Dec 2024
  • Publisher: Springer Verlag Singapore
  • Publication City/Country: Singapore
  • Language: English
  • ISBN13: 9789819782802

About Dong Shen

Dong Shen received the B.S. degree in mathematics from the School of Mathematics Shandong University Jinan China in 2005 and the Ph.D. degree in mathematics from the Academy of Mathematics and Systems Science Chinese Academy of Sciences (CAS) Beijing China in 2010. From 2010 to 2012 he was a postdoctoral fellow with the Institute of Automation CAS. From 2012 to 2019 he was with the College of Information Science and Technology Beijing University of Chemical Technology Beijing. In 2016 and 2019 he was a visiting scholar with the National University of Singapore Singapore and RMIT University Melbourne VIC Australia respectively. Since 2020 he has been a professor at the School of Mathematics Renmin University of China Beijing. His research interests include iterative learning control stochastic optimization stochastic systems and distributed artificial intelligence.

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