article · IEEE Transactions on Systems Man and Cybernetics Systems · 2020
Hamiltonian-Driven Hybrid Adaptive Dynamic Programming
Yongliang Yang, Kyriakos G. Vamvoudakis, Hamidreza Modares, Yixin Yin, Donald C. Wunsch
Cited by 80Abstract and details only
Abstract
This article presents a model-based hybrid adaptive dynamic programming (ADP) framework consisting of continuous feedback-based policy evaluation and policy improvement steps as well as an intermittent policy implementation procedure. This results in an intermittent ADP with a quantifiable performance and guaranteed closed-loop stability of the equilibrium point. To investigate the effect of aperiodic sampling on the communication bandwidth and the control performance of the intermittent ADP algorithms, we use a Hamiltonian-driven unified framework. With such a framework, it is shown that there is a tradeoff between the communication burden and the control performance. We finally show that the developed policies exhibit Zeno-free behaviors. Simulation examples show the efficiency of the proposed framework along with quantifiable comparisons of the policies with different intermittent information.
Cite this paper
Yang, Y., Vamvoudakis, K. G., Modares, H., Yin, Y., & Wunsch, D. C. (2020). Hamiltonian-Driven Hybrid Adaptive Dynamic Programming. IEEE Transactions on Systems Man and Cybernetics Systems, 51(10), 6423–6434. https://doi.org/10.1109/tsmc.2019.2962103
Yang, Yongliang, et al. “Hamiltonian-Driven Hybrid Adaptive Dynamic Programming.” IEEE Transactions on Systems Man and Cybernetics Systems, vol. 51, no. 10, 2020, pp. 6423–34, https://doi.org/10.1109/tsmc.2019.2962103.
Yang, Yongliang, Kyriakos G. Vamvoudakis, Hamidreza Modares, Yixin Yin, and Donald C. Wunsch. 2020. “Hamiltonian-Driven Hybrid Adaptive Dynamic Programming.” IEEE Transactions on Systems Man and Cybernetics Systems 51 (10): 6423–34. https://doi.org/10.1109/tsmc.2019.2962103.
Yang, Y. et al. (2020) ‘Hamiltonian-Driven Hybrid Adaptive Dynamic Programming’, IEEE Transactions on Systems Man and Cybernetics Systems, 51(10), pp. 6423–6434. Available at: https://doi.org/10.1109/tsmc.2019.2962103.
@article{yang2020hamiltonian,
title = {{Hamiltonian-Driven Hybrid Adaptive Dynamic Programming}},
author = {Yang, Yongliang and Vamvoudakis, Kyriakos G. and Modares, Hamidreza and Yin, Yixin and Wunsch, Donald C.},
journal = {IEEE Transactions on Systems Man and Cybernetics Systems},
volume = {51},
number = {10},
pages = {6423--6434},
year = {2020},
doi = {10.1109/tsmc.2019.2962103}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.