Hamiltonian-Driven Hybrid Adaptive Dynamic Programming

Hamiltonian-Driven Hybrid Adaptive Dynamic Programming
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哈密​​顿驱动的混合自适应动态规划

DOI:
10.1109/tsmc.2019.2962103
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发表时间:
2020-01
期刊:
IEEE Transactions on Systems, Man, and Cybernetics: Systems
影响因子:
--
通讯作者:
Donald C. Wunsch
Donald C. Wunsch
中科院分区:
其他
文献类型:
--
作者:
Yongliang Yang;Kyriakos G. Vamvoudakis;Hamidreza Modares;Yixin Yin;Donald C. Wunsch

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本文提出了一个基于模型的混合自适应动态规划(ADP)框架,该框架由连续的基于反馈的策略评估和策略改进步骤以及间歇的策略实施过程组成。这导致间歇性ADP具有可量化的性能和保证平衡点的闭环稳定性。为了研究非周期采样对间歇ADP算法的通信带宽和控制性能的影响,我们使用了一个哈密顿驱动的统一框架。在这种框架下,通信负担和控制性能之间存在着一种权衡。我们最后表明,发达的政策表现出无芝诺行为。仿真实例表明了该框架的有效性,并对不同间歇信息下的策略进行了可量化的比较。
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.
DOI: 10.1109/jas.2014.7004686
发表时间: 2014-07
期刊: IEEE/CAA Journal of Automatica Sinica
影响因子: --
作者:
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