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

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

12.01.2019

Abbildungen

XVIII, 86 illus., 73 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Verlag

Springer Singapore

Seitenzahl

230

Maße (L/B/H)

23,5/15,5/1,4 cm

Gewicht

388 g

Auflage

Softcover reprint of the original 1st edition 2018

Sprache

Englisch

ISBN

978-981-13-5043-6

Beschreibung

Rezension

“Book contains various real-world examples to illustrate the developed mathematical analysis. Thus, it is a valuable and important guide for engineers, researchers, and students in systems, decision and control science.” (Savin Treanta, zbMATH 1403.49002, 2019)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

12.01.2019

Abbildungen

XVIII, 86 illus., 73 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen

Verlag

Springer Singapore

Seitenzahl

230

Maße (L/B/H)

23,5/15,5/1,4 cm

Gewicht

388 g

Auflage

Softcover reprint of the original 1st edition 2018

Sprache

Englisch

ISBN

978-981-13-5043-6

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Self-Learning Optimal Control of Nonlinear Systems
  • Produktbild: Self-Learning Optimal Control of Nonlinear Systems
  • 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.