A Novel PID Neural Network Controller based on Memristor

被引：0

作者：

Geng Yangyang ^{[1
]}

Duan Shukai ^{[1
]}

Dong Zhekang ^{[2
]}

Wang Lidan ^{[1
]}

机构：

[1] Southwest Univ, Coll Elect & Informat Engn, Chongqing 400715, Peoples R China

[2] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China

来源：

PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年

基金：

中国国家自然科学基金;

关键词：

Memristor; adaptive PID neural network; Chaotic Particle Swarm Optimization algorithm; automatic voltage regulation system;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, an effective optimize method based on adaptive PID neural network controller is presented. Chaotic Particle Swarm Optimization (CPSO) is introduced to initialize the parameters of neural network for improving the convergent speed and preventing weights trapping into local optima. In order to realize the hardware platform of PID neural network controller and facilitate weight update algorithm, the nanoscale memristor is utilized to analog electronic synapse. Meanwhile, the stability of closed-loop system is further proved by Lyapunov theory. Based on several comparative experiments on automatic voltage regulation system, the final results illustrate that the proposed controller can obtain better precision in a shorter time.

引用

页码：3988 / 3993

页数：6

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