Spiking Adaptive Dynamic Programming Based on Poisson Process for Discrete-Time Nonlinear Systems | IEEE Journals & Magazine | IEEE Xplore

Spiking Adaptive Dynamic Programming Based on Poisson Process for Discrete-Time Nonlinear Systems


Abstract:

In this article, a new iterative spiking adaptive dynamic programming (SADP) method based on the Poisson process is developed to solve optimal impulsive control problems....Show More

Abstract:

In this article, a new iterative spiking adaptive dynamic programming (SADP) method based on the Poisson process is developed to solve optimal impulsive control problems. For a fixed time interval, combining the Poisson process and the maximum likelihood estimation (MLE), the three-tuple of state, spiking interval, and probability of Poisson distribution can be computed, and then, the iterative value functions and iterative control laws can be obtained. A property analysis method is developed to show that the value functions converge to optimal performance index function as the iterative index increases from zero to infinity. Finally, two simulation examples are given to verify the effectiveness of the developed algorithm.
Page(s): 1846 - 1856
Date of Publication: 18 June 2021

ISSN Information:

PubMed ID: 34143743

Funding Agency:


References

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