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Spiking Adaptive Dynamic Programming with Poisson Process

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Advances in Swarm Intelligence (ICSI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12690))

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Abstract

A new iterative spiking adaptive dynamic programming (SADP) algorithm based on the Poisson process for optimal impulsive control problems is investigated with convergence discussion of the iterative process. For a fixed time interval, a 3-tuple can be computed, and then the iterative value functions and control laws can be obtained. Finally, a simulation example verifies the effectiveness of the developed algorithm.

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Author information

Authors and Affiliations

  1. The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Qinglai Wei & Liyuan Han

  2. Institute of Systems Engineering, Macau University of Science and Technology, Macau, 999078, China

    Qinglai Wei

  3. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China

    Liyuan Han

  4. Research Center for Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Tielin Zhang

Authors
  1. Qinglai Wei
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  2. Liyuan Han
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  3. Tielin Zhang
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Corresponding author

Correspondence to Qinglai Wei .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Wei, Q., Han, L., Zhang, T. (2021). Spiking Adaptive Dynamic Programming with Poisson Process. In: Tan, Y., Shi, Y. (eds) Advances in Swarm Intelligence. ICSI 2021. Lecture Notes in Computer Science(), vol 12690. Springer, Cham. https://doi.org/10.1007/978-3-030-78811-7_49

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  • DOI: https://doi.org/10.1007/978-3-030-78811-7_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78810-0

  • Online ISBN: 978-3-030-78811-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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