Spiking Neural PID Controllers

被引：0

作者：

Webb, Andrew ^{[1
]}

Davies, Sergio ^{[1
]}

Lester, David ^{[1
]}

机构：

[1] Univ Manchester, Sch Comp Sci, Manchester, Lancs, England

来源：

NEURAL INFORMATION PROCESSING, PT III | 2011年 / 7064卷

基金：

英国工程与自然科学研究理事会;

关键词：

SpiNNaker; neural networks; PID controllers; NEURONS; SYSTEMS; MODEL;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A PID controller is a simple and general-purpose way of providing responsive control of dynamic systems with reduced overshoot and oscillation. Spiking neural networks offer some advantages for dynamic systems control, including an ability to adapt, but it is not obvious how to alter such a control network's parameters to shape its response curve. In this paper we present a spiking neural PID controller: a small network of neurons that mimics a PID controller by using the membrane recovery variable in Izhikevich's simple model of spiking neurons to approximate derivative and integral functions.

引用

页码：259 / 267

页数：9

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