03278nam a22006135i 4500 978-981-97-8281-9 DE-He213 20251030114919.0 cr nn 008mamaa 250103s2024 si | s |||| 0|eng d 9789819782819 978-981-97-8281-9 10.1007/978-981-97-8281-9 doi TJ212-225 TJFM bicssc GPFC bicssc TEC007000 bisacsh TJFM thema Shen, Dong. author. aut http://id.loc.gov/vocabulary/relators/aut 90107 Variable Gain Design in Stochastic Iterative Learning Control [electronic resource] / by Dong Shen. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XI, 350 p. 101 illus., 100 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Intelligent Control and Learning Systems, 2662-5466 ; 13 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. Control engineering. Stochastic processes. 76770 System theory. 66519 Control theory. 68675 Industrial engineering. Automation. 59149 Control and Systems Theory. 65868 Stochastic Systems and Control. 87229 Systems Theory, Control. 68676 Industrial Automation. 66585 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819782802 Printed edition: 9789819782826 Printed edition: 9789819782833 Intelligent Control and Learning Systems, 2662-5466 ; 13 74070 https://doi.org/10.1007/978-981-97-8281-9 ZDB-2-INR ZDB-2-SXIT 66319 66319