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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis
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Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis

机译：离散时间局部值迭代自适应动态规划：可容许性和终止性分析

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摘要

In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.
机译：为了解决离散时间非线性系统的无限水平最优控制问题，本文提出了一种新的局部值迭代自适应动态规划算法。本文的重点是研究离散时间局部值迭代ADP算法的可容许性和终止准则。在离散时间局部值迭代ADP算法中，迭代值函数和迭代控制律都在每次迭代中在状态空间的给定子集中而不是在整个状态空间中更新。首次针对局部值迭代ADP算法分析了迭代控制律的可容许性。建立新的终止标准，以允许的近似最佳控制定律终止迭代局部ADP算法。最后，仿真结果说明了所开发算法的性能。

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