神经网络与制动模式下调节轮滑过程模型中的微分对策要素

A. Fedin, Y. Kalinin, E. Marchuk
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引用次数: 1

摘要

地面轮式车辆制动系统的运行过程是一个复杂的非线性动态过程。在求解车辆制动过程建模问题时,将其设置为一种对抗微分对策的形式,并将其中一个对抗者(路面)表示为一种未知扰动的形式是合理的。选择人工神经网络作为控制单元和具有自学习特性的柔性逼近器是合理的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ANN and elements of differentional games in the model of regulated wheel slippage process in a braking mode
Processes of braking system operations of the ground wheeled vehicle are complex nonlinear dynamic processes. When a problem of modeling vehicle braking process is setting it is considered rational to set the one in a form of the antagonistic differential game and to represent one of the antagonists - the road surface - in a form of unknown disturbance. It is considered rational to choose an artificial neural network (ANN) as a control element and flexible approximator that has properties of self-learning.
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