一类非线性离散时滞系统的启发式动态规划最优跟踪控制。

IEEE transactions on neural networks Pub Date : 2011-12-01 Epub Date: 2011-11-01 DOI:10.1109/TNN.2011.2172628
Huaguang Zhang, Ruizhuo Song, Qinglai Wei, Tieyan Zhang
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引用次数: 172

摘要

针对一类非线性离散时滞系统的最优跟踪控制问题,提出了一种新的启发式动态规划(HDP)迭代算法。该算法包含状态更新、控制策略迭代和性能指标迭代。为了获得最佳状态,状态也会被更新。此外,将“向后迭代”应用于状态更新。利用两个神经网络逼近性能指标函数,计算最优控制策略,便于HDP迭代算法的实现。最后,通过两个算例验证了所提出的HDP迭代算法的有效性。
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Optimal tracking control for a class of nonlinear discrete-time systems with time delays based on heuristic dynamic programming.

In this paper, a novel heuristic dynamic programming (HDP) iteration algorithm is proposed to solve the optimal tracking control problem for a class of nonlinear discrete-time systems with time delays. The novel algorithm contains state updating, control policy iteration, and performance index iteration. To get the optimal states, the states are also updated. Furthermore, the "backward iteration" is applied to state updating. Two neural networks are used to approximate the performance index function and compute the optimal control policy for facilitating the implementation of HDP iteration algorithm. At last, we present two examples to demonstrate the effectiveness of the proposed HDP iteration algorithm.

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来源期刊
IEEE transactions on neural networks
IEEE transactions on neural networks 工程技术-工程:电子与电气
自引率
0.00%
发文量
2
审稿时长
8.7 months
期刊最新文献
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