Deep Reinforcement Learning with Guaranteed Performance: A Lyapunov-Based Approach:A Lyapunov-Based Approach(Studies in Systems, Decision and Control)

深度强化学习与保证表现:基于李雅普诺夫的方法

人工智能

原   价:
2511.25
售   价:
2009.00
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平台大促 低至8折优惠
发货周期:外国库房发货,通常付款后3-5周到货
作      者
出  版 社
出版时间
2019年11月20日
装      帧
精装
ISBN
9783030333836
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页      码
225
开      本
9.21 x 6.14 x 0.56
语      种
英文
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图书简介
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.
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