非线性倒立摆系统的人工神经网络辨识

Pooja Gautam
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引用次数: 8

摘要

系统识别是利用系统的输入和输出知识建立系统数学模型的过程。由于非线性系统的不可预测性和复杂性,辨识是一个众所周知的问题。本文所采用的非线性辨识系统为倒立摆,由于其高度非线性和不稳定的特性,倒立摆在控制系统理论中被称为基准系统。在这项工作中,拉格朗日方法已被用于系统动态建模。利用人工神经网络对模型进行识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
System identification of nonlinear Inverted Pendulum using artificial neural network
System identification is the process of developing a mathematical model of a system using input and output knowledge of system. Identification of nonlinear system is well known problem due to its unpredictability and complexity. The nonlinear system for identification is Inverted Pendulum in this work which is well known benchmark system in control system theory due to it's highly nonlinear and unstable characteristics. In this work Lagrangian approach has been used for system dynamic modelling. Artificial neural network is utilized for model identification.
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