Learning Control Applications in Robotics and Complex Dynamical Systems 1st Edition – Ebook PDF Instant Delivery – ISBN(s): 9780128223154,0128223154
Product details:
- ISBN-10 : 0128223154
- ISBN-13 : 9780128223154
- Author: Dan Zhang , Bin Wei
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.
Table of contents:
Chapter 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
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