Analysis And Synthesis Of Reset Control Systems


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Analysis and Synthesis of Reset Control Systems


Analysis and Synthesis of Reset Control Systems

Author: Christophe Prieur

language: en

Publisher:

Release Date: 2018


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Control Strategy for Time-Delay Systems


Control Strategy for Time-Delay Systems

Author: Mohammad-Hassan Khooban

language: en

Publisher: Academic Press

Release Date: 2020-11-27


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Since delays are present in 99% of industrial processes, Control Strategy for Time-delay Systems covers all the important features of real-world practical applications which will be valuable to practicing engineers and specialists The book presents the views of the editors on promising research directions and future industrial applications in this area. Although the fundamentals of time-delay systems are discussed, the book focuses on the advanced modelling and control of such systems and will provide the analysis and test (or simulation) results of nearly every technique described in the book For this purpose, highly complex models are introduced to ?describe the mentioned new applications which are characterized by ?time-varying delays with intermittent and stochastic nature, several types of nonlinearities, and the presence ?of different time-scales. Researchers, practitioners and PhD students will gain insights into the prevailing trends in design and operation of real-time control systems, reviewing the shortcomings and future developments concerning the practical system issues such as standardization, protection and design.

Handbook of Reinforcement Learning and Control


Handbook of Reinforcement Learning and Control

Author: Kyriakos G. Vamvoudakis

language: en

Publisher: Springer Nature

Release Date: 2021-06-23


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This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology. The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including: deep learning; artificial intelligence; applications of game theory; mixed modality learning; and multi-agent reinforcement learning. Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.