Neural Dynamic Programming for Event-Based Nonlinear Adaptive Robust Stabilization

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• 关键词：Adaptive dynamic programming ; Adaptive robust stabilization ; Event ; based control ; Neural dynamic programming ; Neural network
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9947
• 期：1
• 页码：149-157
• 全文大小：265 KB
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• 作者单位：Ding Wang (19)
  Hongwen Ma (19)
  Derong Liu (20)
  Huidong Wang (21)
  
  19. The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
  20. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China
  21. School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan, 250014, China
  
• 丛书名：Neural Information Processing
• ISBN：978-3-319-46687-3
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9947

文摘

In this paper, we develop an event-based adaptive robust stabilization method for continuous-time nonlinear systems with uncertain terms via a self-learning technique called neural dynamic programming. Through system transformation, it is proven that the robustness of the uncertain system can be achieved by designing an event-triggered optimal controller with respect to the nominal system under a suitable triggering condition. Then, the idea of neural dynamic programming is adopted to perform the main controller design task by building and training a critic network. Finally, the effectiveness of the present adaptive robust control strategy is illustrated via a simulation example.