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Self-Learning Optimal Control of Nonlinear Systems: Adaptive Dynamic Programming Approach

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Personen und Körperschaften: Wei, Qinglai (VerfasserIn), Song, Ruizhuo (Sonstige), Li, Benkai (Sonstige), Lin, Xiaofeng (Sonstige)
Titel: Self-Learning Optimal Control of Nonlinear Systems: Adaptive Dynamic Programming Approach/ by Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
Format: E-Book
Sprache: Englisch
veröffentlicht:
Singapore Springer 2018
Gesamtaufnahme: Studies in Systems, Decision and Control
SpringerLink
Springer eBook Collection
Schlagwörter:
Engineering
Computational intelligence
Vibration
Dynamical systems
Dynamics
Control engineering
Quelle: Verbunddaten SWB
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contents This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum. With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering, Chapter 1. Principle of Adaptive Dynamic Programming -- Chapter 2. An Iterative ϵ-Optimal Control Scheme for a Class of Discrete-Time Nonlinear Systems With Unfixed Initial State -- Chapter 3. Discrete-Time Optimal Control of Nonlinear Systems Via Value Iteration-Based Q-Learning -- Chapter 4. A Novel Policy Iteration Based Deterministic Q-Learning for Discrete-Time Nonlinear Systems -- Chapter 5. Nonlinear Neuro-Optimal Tracking Control Via Stable Iterative Q-Learning Algorithm -- Chapter 6. Model-Free Multiobjective Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems with General Performance Index Functions -- Chapter 7. Multi-Objective Optimal Control for a Class of Unknown Nonlinear Systems Based on Finite-Approximation-Error ADP Algorithm -- Chapter 8. A New Approach for a Class of Continuous-Time Chaotic Systems Optimal Control by Online ADP Algorithm -- Chapter 9. Off-Policy IRL Optimal Tracking Control for Continuous-Time Chaotic Systems -- Chapter 10. ADP-Based Optimal Sensor Scheduling for Target Tracking in Energy Harvesting Wireless Sensor Networks
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spelling Wei, Qinglai aut, Self-Learning Optimal Control of Nonlinear Systems Adaptive Dynamic Programming Approach by Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin, Singapore Springer 2018, Online-Ressource (XVI, 230 p. 86 illus., 73 illus. in color, online resource), Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, Studies in Systems, Decision and Control 103, SpringerLink Bücher, Springer eBook Collection Engineering, This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum. With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering, Chapter 1. Principle of Adaptive Dynamic Programming -- Chapter 2. An Iterative ϵ-Optimal Control Scheme for a Class of Discrete-Time Nonlinear Systems With Unfixed Initial State -- Chapter 3. Discrete-Time Optimal Control of Nonlinear Systems Via Value Iteration-Based Q-Learning -- Chapter 4. A Novel Policy Iteration Based Deterministic Q-Learning for Discrete-Time Nonlinear Systems -- Chapter 5. Nonlinear Neuro-Optimal Tracking Control Via Stable Iterative Q-Learning Algorithm -- Chapter 6. Model-Free Multiobjective Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems with General Performance Index Functions -- Chapter 7. Multi-Objective Optimal Control for a Class of Unknown Nonlinear Systems Based on Finite-Approximation-Error ADP Algorithm -- Chapter 8. A New Approach for a Class of Continuous-Time Chaotic Systems Optimal Control by Online ADP Algorithm -- Chapter 9. Off-Policy IRL Optimal Tracking Control for Continuous-Time Chaotic Systems -- Chapter 10. ADP-Based Optimal Sensor Scheduling for Target Tracking in Energy Harvesting Wireless Sensor Networks, Engineering, Computational intelligence, Vibration, Dynamical systems, Dynamics, Control engineering, Song, Ruizhuo oth, Li, Benkai oth, Lin, Xiaofeng oth, 9789811040795, Druckausg. 978-981-10-4079-5, Printed edition 9789811040795, https://doi.org/10.1007/978-981-10-4080-1 B:SPRINGER Verlag lizenzpflichtig Volltext, https://swbplus.bsz-bw.de/bsz490766080cov.jpg V:DE-576 X:springer image/jpeg 20180205130702 Cover, https://zbmath.org/?q=an:1403.49002 B:ZBM 2021-04-12 Verlag Zentralblatt MATH Inhaltstext, (DE-627)892482877, https://doi.org/10.1007/978-981-10-4080-1 DE-14, DE-14 epn:3421854149 2019-05-09T16:02:16Z, http://dx.doi.org/10.1007/978-981-10-4080-1 DE-Ch1, DE-Ch1 epn:3409047646 2017-12-07T13:35:29Z, DE-105 epn:3409047794 2018-03-12T17:32:05Z, http://dx.doi.org/10.1007/978-981-10-4080-1 DE-Zwi2, DE-Zwi2 epn:3409048103 2018-01-24T15:50:17Z
spellingShingle Wei, Qinglai, Self-Learning Optimal Control of Nonlinear Systems: Adaptive Dynamic Programming Approach, This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum. With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering, Chapter 1. Principle of Adaptive Dynamic Programming -- Chapter 2. An Iterative ϵ-Optimal Control Scheme for a Class of Discrete-Time Nonlinear Systems With Unfixed Initial State -- Chapter 3. Discrete-Time Optimal Control of Nonlinear Systems Via Value Iteration-Based Q-Learning -- Chapter 4. A Novel Policy Iteration Based Deterministic Q-Learning for Discrete-Time Nonlinear Systems -- Chapter 5. Nonlinear Neuro-Optimal Tracking Control Via Stable Iterative Q-Learning Algorithm -- Chapter 6. Model-Free Multiobjective Adaptive Dynamic Programming for Discrete-Time Nonlinear Systems with General Performance Index Functions -- Chapter 7. Multi-Objective Optimal Control for a Class of Unknown Nonlinear Systems Based on Finite-Approximation-Error ADP Algorithm -- Chapter 8. A New Approach for a Class of Continuous-Time Chaotic Systems Optimal Control by Online ADP Algorithm -- Chapter 9. Off-Policy IRL Optimal Tracking Control for Continuous-Time Chaotic Systems -- Chapter 10. ADP-Based Optimal Sensor Scheduling for Target Tracking in Energy Harvesting Wireless Sensor Networks, Engineering, Computational intelligence, Vibration, Dynamical systems, Dynamics, Control engineering
swb_id_str 490766080
title Self-Learning Optimal Control of Nonlinear Systems: Adaptive Dynamic Programming Approach
title_auth Self-Learning Optimal Control of Nonlinear Systems Adaptive Dynamic Programming Approach
title_full Self-Learning Optimal Control of Nonlinear Systems Adaptive Dynamic Programming Approach by Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
title_fullStr Self-Learning Optimal Control of Nonlinear Systems Adaptive Dynamic Programming Approach by Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
title_full_unstemmed Self-Learning Optimal Control of Nonlinear Systems Adaptive Dynamic Programming Approach by Qinglai Wei, Ruizhuo Song, Benkai Li, Xiaofeng Lin
title_short Self-Learning Optimal Control of Nonlinear Systems
title_sort self-learning optimal control of nonlinear systems adaptive dynamic programming approach
title_sub Adaptive Dynamic Programming Approach
title_unstemmed Self-Learning Optimal Control of Nonlinear Systems: Adaptive Dynamic Programming Approach
topic Engineering, Computational intelligence, Vibration, Dynamical systems, Dynamics, Control engineering
topic_facet Engineering, Computational intelligence, Vibration, Dynamical systems, Dynamics, Control engineering
url https://doi.org/10.1007/978-981-10-4080-1, https://swbplus.bsz-bw.de/bsz490766080cov.jpg, https://zbmath.org/?q=an:1403.49002, http://dx.doi.org/10.1007/978-981-10-4080-1
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