计算机技术与发展Issue(9)：158-161,4.DOI:10.3969/j.issn.1673-629X.2013.09.040
基于粒子群算法的PID神经网络解耦控制
PID Neural Network Decoupling Control Based on Particle Swarm Optimization
摘要
Abstract
The automatic control of such a system is a research focus in the process control area. A multivariable adaptive PID Artificial Neural Network ( ANN) controller was introduced,which was based on the characteristics of Particle Swarm Optimization ( PSO) algo-rithm searching the parameter space concurrently and efficiently,and the self-regulation and adaptability of PID artificial neuron net-works. Utilize the PSO to optimize the initial weight value of PID neural network,successfully achieve the control strategy of a nonlinear coupling system using the improved PID neural network with those obtained from the original PID neural network. The new control strate-gy could overcome nonlinear and strong coupling features of the system in a wide range and is expected to have certain theoretical and en-gineering application value.关键词
粒子群算法/PID控制/解耦控制/多变量系统Key words
PSO algorithm/PID control/decoupling control/multivariable system分类
信息技术与安全科学引用本文复制引用
周西峰,林莹莹,郭前岗..基于粒子群算法的PID神经网络解耦控制[J].计算机技术与发展,2013,(9):158-161,4.基金项目
国家自然科学基金资助项目(61105082) （61105082）
