华东理工大学学报：自然科学版2012，Vol.38Issue(6)：729-734,6.
基于QPSO的PID神经网络控制算法及其仿真
PID Neural Network Control Algorithms Based on QPSO and Its Simulation
韩明 1孙京诰2
作者信息
- 1. 邹城市质量技术监督局,山东邹城273500
- 2. 华东理工大学信息科学与工程学院,上海200237
- 折叠
摘要
Abstract
PID neural network (PIDNN) control algorithm is suitable for the decoupling control of nonlinear multivariable coupled system, because of its better dynamic and steady performance, and stronger decoupling and disturbance-attenuate ability. By updating weights via Quantum Particle Swarm Optimization(QPSO), this paper further proposes a multivariable PID neural network control algorithm. The simulation results show that the present algorithm can attain better decoupling control effect and stronger disturbance-attenuate ability.关键词
多变量PID神经元网络/解耦/量子粒子群算法Key words
MPIDNN/decoupling/QPSO分类
信息技术与安全科学引用本文复制引用
韩明,孙京诰..基于QPSO的PID神经网络控制算法及其仿真[J].华东理工大学学报：自然科学版,2012,38(6):729-734,6.
