Variable Gain Design in Stochastic Iterative Learning Control
Shen, Dong.
Variable Gain Design in Stochastic Iterative Learning Control [electronic resource] / by Dong Shen. - 1st ed. 2024. - XI, 350 p. 101 illus., 100 illus. in color. online resource. - Intelligent Control and Learning Systems, 13 2662-5466 ; . - Intelligent Control and Learning Systems, 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.
9789819782819
Control engineering.
Stochastic processes.
System theory.
Control theory.
Industrial engineering.
Automation.
Control and Systems Theory.
Stochastic Systems and Control.
Systems Theory, Control.
Industrial Automation.
TJ212-225
629.8312 003
Variable Gain Design in Stochastic Iterative Learning Control [electronic resource] / by Dong Shen. - 1st ed. 2024. - XI, 350 p. 101 illus., 100 illus. in color. online resource. - Intelligent Control and Learning Systems, 13 2662-5466 ; . - Intelligent Control and Learning Systems, 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.
9789819782819
Control engineering.
Stochastic processes.
System theory.
Control theory.
Industrial engineering.
Automation.
Control and Systems Theory.
Stochastic Systems and Control.
Systems Theory, Control.
Industrial Automation.
TJ212-225
629.8312 003
