Pensum -10%
Hopp til hovedinnholdet
Deep Reinforcement Learning with Guaranteed Performance
Av Shuai Li, Yinyan Zhang, Xuefeng Zhou, 2020.Del av serien Studies in Systems, Decision and Control.
A Lyapunov-Based Approach
This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances. It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution. Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.
Språk: Engelsk
Normalpris: 1 489,-
1 340,-
Spar 149,-
Ikke tilgjengelig for Klikk&Hent
Midlertidig tomt på lager
Bestillingsvare. Forventes sendt om ca 20 dager
Deep Reinforcement Learning with Guaranteed Performance
Av Shuai Li, Yinyan Zhang, Xuefeng Zhou, 2020.Del av serien Studies in Systems, Decision and Control.
A Lyapunov-Based Approach
This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances. It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution. Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.
Normalpris: 1 489,-
1 340,-
Spar 149,-
Språk: Engelsk
Ikke tilgjengelig for Klikk&Hent
Midlertidig tomt på lager
Bestillingsvare. Forventes sendt om ca 20 dager
1 340,-
Ved å fullføre kjøpet aksepterer du kjøpsvilkårene.
