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Model-free multiobjective approximate dynamic programming for discrete-time nonlinear systems with general performance index functions

机译:具有通用性能指标函数的离散时间非线性系统的无模型多目标近似动态规划

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摘要

In this paper, a forward-in-time optimal control method for a class of discrete-time nonlinear systems with general multiobjective performance indices is proposed with unknown system dynamics. The proposed approximate dynamic programming (ADP) method aims to find out the increments of both the controls and states instead of computing the controls and states directly. Using the technique of dimension augment, the vector-valued performance indices are transformed into additive quadratic form which satisfies the corresponding discrete-time algebraic Riccati equation (DTARE). Both the action and critic networks can be adaptively tuned by adaptive critic methods without the information of the system model. The convergence property is guaranteed by a rigorous mathematical proof and finally the simulation results show the effectiveness of the method.
机译:本文针对一类具有一般多目标性能指标的离散时间非线性系统,在系统动力学未知的情况下,提出了一种及时的最优控制方法。所提出的近似动态编程(ADP)方法旨在找出控件和状态的增量,而不是直接计算控件和状态。使用维数扩充技术,将向量值性能指标转换为可满足相应离散时间代数Riccati方程(DTARE)的加法二次形式。动作和评论者网络都可以通过自适应评论者方法进行自适应调整,而无需系统模型的信息。严格的数学证明保证了收敛性,最后的仿真结果证明了该方法的有效性。

著录项

  • 来源
    《Neurocomputing》 |2009年第9期|1839-1848|共10页
  • 作者单位

    School of Information Science and Engineering, Northeastern University Shenyang, Liaoning 110004, People's Republic of China;

    School of Information Science and Engineering, Northeastern University Shenyang, Liaoning 110004, People's Republic of China;

    School of Electrical and Computer Engineering, Georgia Institute of Technology at Atlanta, 801 Atlantic Drive Atlanta, GA 30332-0280, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    multiobjective optimal control; approximate dynamic programming; model-free; q-learning;

    机译:多目标最优控制近似动态规划;无模型q学习;

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