基于神经网络的非线性H/sub /spl输入//控制方法

Xiaofeng Yang, K. Tamura, T. Shen
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引用次数: 1

摘要

本文提出了一种求解非线性H/sub /spl输入//控制问题的神经网络方法。神经网络沿闭环系统的动态轨迹充分在线学习,得到Hamilton-Jacobi不等式的近似解,然后通过神经网络显式实现状态反馈H/sub /spl / infin//控制器。为了保证系统在网络学习过程中的稳定性,提出了一种结合线性H/sub /spl / infin//控制的学习算法。
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An approach to solve nonlinear H/sub /spl infin// control problem based on neural networks
In this paper, a neural network approach to solve nonlinear H/sub /spl infin// control problem is proposed. An approximation solution of the Hamilton-Jacobi inequality can be obtained after neural network online learning along dynamic trajectories of closed-loop system sufficiently, then the state feedback H/sub /spl infin// controller is explicitly realized by the neural networks. In order to ensuring the stability of system during learning procedure of network, a learning algorithm combined with linear H/sub /spl infin// control is given.
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