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...
| Hoofdauteurs: | , , |
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| Formaat: | software, multimedia |
| Taal: | eng |
| Gepubliceerd in: |
Amsterdam : Elsevier,
2021
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| Onderwerpen: | |
| Online toegang: | https://www.sciencedirect.com/science/book/9780128223147 |
| _version_ | 1826472428282314752 |
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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. |
| first_indexed | 2024-03-05T17:18:21Z |
| format | software, multimedia |
| id | KOHA-OAI-TEST:605817 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T17:18:21Z |
| publishDate | 2021 |
| publisher | Amsterdam : Elsevier, |
| record_format | dspace |
| 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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