Jagannathan S Optimal Event-Triggered Control Using Adaptive Dynamic Prog 2024

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Jagannathan S  Optimal Event-Triggered Control Using Adaptive Dynamic Prog <span style=color:#777> 2024</span>Jagannathan S  Optimal Event-Triggered Control Using Adaptive Dynamic Prog <span style=color:#777> 2024</span>

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Jagannathan S Optimal Event-Triggered Control Using Adaptive Dynamic Prog 2024.torrent
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Optimal Event-triggered Control using Adaptive Dynamic Programming discusses event triggered controller design which includes optimal control and event sampling design for linear and nonlinear dynamic systems including networked control systems (NCS) when the system dynamics are both known and uncertain. The NCS are a first step to realize cyber-physical systems (CPS) or industry 4.0 vision. The authors apply several powerful modern control techniques to the design of event-triggered controllers and derive event-trigger condition and demonstrate closed-loop stability. Detailed derivations, rigorous stability proofs, computer simulation examples, and downloadable MatLAB codes are included for each case. The book begins by providing background on linear and nonlinear systems, NCS, networked imperfections, distributed systems, adaptive dynamic programming and optimal control, stability theory, and optimal adaptive event-triggered controller design in continuous-time and discrete-time for linear, nonlinear and distributed systems. It lays the foundation for reinforcement learning-based optimal adaptive controller use for infinite horizons. An ideal textbook for senior undergraduate students, graduate students, university researchers, and practicing engineers, Optimal Event Triggered Control Design using Adaptive Dynamic Programming instills a solid understanding of neural network-based optimal controllers under event-sampling and how to build them so as to attain CPS or Industry 4.0 vision.
Background and Introduction to Event-triggered Control
Adaptive Dynamic Programming and Optimal Control
Linear Discrete-time and Networked Control Systems
Nonlinear Continuous-time Systems
Co-optimization of Event-triggered Sampling and Control
Linear Interconnected Systems
Nonlinear Interconnected Systems
Exploration and Hybrid Learning for Nonlinear Interconnected Systems
Event-Triggered Control Applications

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