基于PID神经网络的多变量系统辨识

Huailin Shu, Xiaogang Wang, Zihang Huang
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引用次数: 3

摘要

系统辨识是控制系统设计的基础。对于线性定常系统有多种辨识方法,对于非线性动态系统的辨识方法还处于探索阶段。基于神经网络的非线性辨识方法是一种简单有效的通用方法,不需要对系统进行过多的先验经验即可进行辨识。通过训练和学习,对网络权值进行修正,达到系统辨识的目的。本文研究了基于PID神经网络的多变量非线性动态系统辨识。介绍了PID神经网络的结构和算法,分析了PID神经网络的特性和特点。完成了系统辨识,结果收敛速度快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of multivariate system based on PID neural network
System identification is the basis for control system design. For linear time-invariant systems have a variety of identification methods, identification methods for nonlinear dynamic system is still in the exploratory stage. Nonlinear identification method based on neural network is a simple and effective general method that does not require too much priori experience about the system to be identified. Through training and learning, the network weights are corrected to achieve the purpose of system identification. The paper is about the identification of multivariable nonlinear dynamic system based on PID neural network. The structure and algorithm of PID neural network are introduced and the properties and characteristics are analyzed. The system identification is completed and the results are fast convergence.
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