9781032468655 - Optimal Event-Triggered Control Using Adaptive Dynamic Programming di Jagannathan, Sarangapani; Narayanan, Vignesh; Sahoo, Avimanyu (17 risultati)

hardcover. Condizione: Fine.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Condizione: New.

Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New. In.

Condizione: New.

Hardcover. Condizione: Brand New. 344 pages. 9.19x6.13x10.00 inches. In Stock.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. The text then:Introduces event triggered control of linear and nonlinear systems, describing the design of adaptive controllers for themPresents neural network-based optimal adaptive control and game theoretic formulation of linear and nonlinear systems enclosed by a communication networkAddresses the stochastic optimal control of linear and nonlinear NCS by using neuro dynamic programmingExplores optimal adaptive design for nonlinear two-player zero-sum games under communication constraints to solve optimal policy and event trigger conditionTreats an event-sampled distributed linear and nonlinear systems to minimize transmission of state and control signals within the feedback loop via the communication networkCovers several examples along the way and provides applications of event triggered control of robot manipulators, UAV and distributed joint optimal network scheduling and control design for wireless NCS/CPS in order to realize industry 4.0 visionAn 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. 348 pp. Englisch.

HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. PRINT ON DEMAND.

Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. The text then:Introduces event triggered control of linear and nonlinear systems, describing the design of adaptive controllers for themPresents neural network-based optimal adaptive control and game theoretic formulation of linear and nonlinear systems enclosed by a communication networkAddresses the stochastic optimal control of linear and nonlinear NCS by using neuro dynamic programmingExplores optimal adaptive design for nonlinear two-player zero-sum games under communication constraints to solve optimal policy and event trigger conditionTreats an event-sampled distributed linear and nonlinear systems to minimize transmission of state and control signals within the feedback loop via the communication networkCovers several examples along the way and provides applications of event triggered control of robot manipulators, UAV and distributed joint optimal network scheduling and control design for wireless NCS/CPS in order to realize industry 4.0 visionAn 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.