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Synopsis
Learning Control: Applications in Robotics and Complex Dynamical Systems provides a foundational understanding of control theory while also introducing exciting cutting-edge technologies in the field of learning-based control. State-of-the-art techniques involving machine learning and artificial intelligence (AI) are covered, as are foundational control theories and more established techniques such as adaptive learning control, reinforcement learning control, impedance control, and deep reinforcement control. Each chapter includes case studies and real-world applications in robotics, AI, aircraft and other vehicles and complex dynamical systems. Computational methods for control systems, particularly those used for developing AI and other machine learning techniques, are also discussed at length.
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À propos des auteurs
Dan Zhang is a Kaneff Professor and Tier 1 York Research Chair in Advanced Robotics and Mechatronics in the Department of Mechanical Engineering of the Lassonde School of Engineering at York University, Toronoto, Canada. Previously he was Professor and Canada Research Chair in Advanced Robotics and Automation, and he was a founding Chair of the Department of Automotive, Mechanical, and Manufacturing Engineering with the Faculty of Engineering and Applied Science at University of Ontario Institute of Technology. He is editor-in-chief for International Journal of Robotics Applications and Technologies, Associate editor for the International Journal of Robotics and Automation (ACTA publisher), and guest editor on four other international journals. He is the editor of 6 books related to mechatronics and robotics.
Bin Wei is an Assistant Professor at Algoma University, Ontario, Canada. He received his Ph.D. in robotics from University of Ontario Institute of Technology, Canada, in 2016. He conducts research in the areas of robotics, control theory, and computational mechanics. He has co-edited 5 books on robotic mechanics.
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- ÉditeurElsevier Science Publishing Co Inc
- Date d'édition2020
- ISBN 10 0128223146
- ISBN 13 9780128223147
- ReliureBroché
- Langueanglais
- Nombre de pages280
- ÉditeurZhang Dan, Wei Bin
- Coordonnées du fabricantnon disponible
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Learning Control: Applications in Robotics and Complex Dynamical Systems
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Elsevier Science & Technology|Elsevier, 2020
ISBN 10 : 0128223146
ISBN 13 : 9780128223147
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Learning Control: Applications in Robotics and Complex Dynamical Systems provides a foundational understanding of control theory while also introducing exciting cutting-edge technologies in the field of learning-based control. State-of-the-art techni. N° de réf. du vendeur 388985672
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Learning Control
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Elsevier Science & Technology, Elsevier, 2020
ISBN 10 : 0128223146
ISBN 13 : 9780128223147
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Learning Control: Applications in Robotics and Complex Dynamical Systems provides a foundational understanding of control theory while also introducing exciting cutting-edge technologies in the field of learning-based control. State-of-the-art techniques involving machine learning and artificial intelligence (AI) are covered, as are foundational control theories and more established techniques such as adaptive learning control, reinforcement learning control, impedance control, and deep reinforcement control. Each chapter includes case studies and real-world applications in robotics, AI, aircraft and other vehicles and complex dynamical systems. Computational methods for control systems, particularly those used for developing AI and other machine learning techniques, are also discussed at length. Englisch. N° de réf. du vendeur 9780128223147
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Learning Control: Applications in Robotics and Complex Dynamical Systems
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Learning Control : Applications in Robotics and Complex Dynamical Systems
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ISBN 13 : 9780128223147
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Learning Control: Applications in Robotics and Complex Dynamical Systems provides a foundational understanding of control theory while also introducing exciting cutting-edge technologies in the field of learning-based control. State-of-the-art techniques involving machine learning and artificial intelligence (AI) are covered, as are foundational control theories and more established techniques such as adaptive learning control, reinforcement learning control, impedance control, and deep reinforcement control. Each chapter includes case studies and real-world applications in robotics, AI, aircraft and other vehicles and complex dynamical systems. Computational methods for control systems, particularly those used for developing AI and other machine learning techniques, are also discussed at length. N° de réf. du vendeur 9780128223147
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