Learning Control : Applications in Robotics and Complex Dynamical Systems /

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 int...

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Asıl Yazarlar: Zhang, Dan, 1964-, editor 651091, Wei, Bin, 1987-, editor 651092, ScienceDirect (Online service) 7722
Materyal Türü: software, multimedia
Dil:eng
Baskı/Yayın Bilgisi: Amsterdam : Elsevier, 2021
Konular:
Online Erişim:https://www.sciencedirect.com/science/book/9780128223147
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author Zhang, Dan, 1964-, editor 651091
Wei, Bin, 1987-, editor 651092
ScienceDirect (Online service) 7722
author_facet Zhang, Dan, 1964-, editor 651091
Wei, Bin, 1987-, editor 651092
ScienceDirect (Online service) 7722
author_sort Zhang, Dan, 1964-, editor 651091
collection OCEAN
description 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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institution Universiti Teknologi Malaysia - OCEAN
language eng
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publishDate 2021
publisher Amsterdam : Elsevier,
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spelling KOHA-OAI-TEST:6058172023-10-03T04:10:11ZLearning Control : Applications in Robotics and Complex Dynamical Systems / Zhang, Dan, 1964-, editor 651091 Wei, Bin, 1987-, editor 651092 ScienceDirect (Online service) 7722 software, multimedia Electronic books 631902 Amsterdam : Elsevier,©20212021engLearning 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.Includes bibliographical references and indexChapter 1. A high-level design process for neural-network controls through a framework of human personalities -- Chapter 2. Cognitive load estimation for adaptive human–machine system automation -- Chapter 3. Comprehensive error analysis beyond system innovations in Kalman filtering -- Chapter 4. Nonlinear control -- Chapter 5. Deep learning approaches in face analysis -- Chapter 6. Finite multi-dimensional generalized Gamma Mixture Model Learning for feature selection -- Chapter 7. Variational learning of finite shifted scaled Dirichlet mixture models -- Chapter 8. From traditional to deep learning: Fault diagnosis for autonomous vehicles -- Chapter 9. Controlling satellites with reaction wheels -- Chapter 10. Vision dynamics-based learning control.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.Control theoryRoboticsArtificial intelligencehttps://www.sciencedirect.com/science/book/9780128223147URN:ISBN:9780128223147Remote access restricted to users with a valid UTM ID via VPN.
spellingShingle Control theory
Robotics
Artificial intelligence
Zhang, Dan, 1964-, editor 651091
Wei, Bin, 1987-, editor 651092
ScienceDirect (Online service) 7722
Learning Control : Applications in Robotics and Complex Dynamical Systems /
title Learning Control : Applications in Robotics and Complex Dynamical Systems /
title_full Learning Control : Applications in Robotics and Complex Dynamical Systems /
title_fullStr Learning Control : Applications in Robotics and Complex Dynamical Systems /
title_full_unstemmed Learning Control : Applications in Robotics and Complex Dynamical Systems /
title_short Learning Control : Applications in Robotics and Complex Dynamical Systems /
title_sort learning control applications in robotics and complex dynamical systems
topic Control theory
Robotics
Artificial intelligence
url https://www.sciencedirect.com/science/book/9780128223147
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