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 readers to 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 discussed at length, as well. Provides foundational control theory concepts as well as advanced techniques and the latest advances in adaptive controlIntroduces state-of-the-art learning-based control technologies and their applications in robotics and other complex dynamical systemsDemonstrates computational techniques for control systemsCovers iterative learning impedance control in both human-robot interaction as well as for collaborative robots INDICE: 1. Overview and Development of Learning Control 2. Learning-Based Control Methods 3. Iterative Learning Control for Robotics 4. Reinforcement Learning Control for Robotics 5. Intelligent Learning Control for Human-Robot Interaction 6. Learning Based Control for Mobile Robots 7. Learning Based Control for Complex Dynamical Systems 8. Deep Learning Based Control for Robotics and Complex Dynamical Systems 9. Deep Reinforcement Learning for Co-Robots; Learning Based Force Control for Compliant Manipulation 10. Learning Impedance Control in Robotics 11. Iterative Learning Impedance Control for Human-Robot Interaction 12. Iterative Learning Impedance Control for Collaborative Robots 13. Learning Variable Impedance Control in Complex Dynamical Systems 14. Dynamic Programming Principle and Approximate Dynamic Programming 15. Decentralized Reinforcement Learning Control for Robotics 16. Adaptive Learning Control in Complex Dynamical Systems 17. Future Trends in Learning Control in Complex Dynamical Systems and Robotics

• ISBN: 978-0-12-822314-7
• Editorial: Elsevier
• Encuadernacion: Rústica
• Páginas: 550
• Fecha Publicación: 01/02/2021
• Nº Volúmenes: 1
• Idioma: Inglés