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Received:March 09, 2011 Revised:April 06, 2011
Received:March 09, 2011 Revised:April 06, 2011
中文摘要: 针对传统的PID 神经网络(PIDNN)应用范围受限及积分误差规则难以获取的问题。为实现对非线性多变量系统的有效控制,拓展神经网络控制系统的应用范围,提出了基于改进型粒子群算法在PID 神经网络控制系统设计中的解决方案,取代了传统的BP 反向传播算法。仿真结果表明,与传统的PIDNN 相比,系统的稳定性、鲁棒性及精确性都有了明显的提高,该方法有效的提高了PIDNN 控制的使用范围,为智能方法在PID 控制中的应用提出了一个新的参考。
Abstract:The traditional PID neural network (PIDNN) limited the scope of application and integration problems are difficult to obtain the error rule. For the realization of nonlinear multivariable control systems, neural network control system to expand the application range of this paper, based on improved version particle swarm optimization algorithm for PID neural network control system design solution, replacing the traditional BP back the propagation algorithm, simulation results show that compared with traditional PIDNN, the steady-state system, robustness and accuracy have improved obviously, this method is effective to improve the use of PID control, intelligent method for the PID Control proposed a new reference.
keywords: PID neural network improved version particle swarm optimization algorithm nonlinear control systems stability accuracy
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基金项目:2009 年度中国煤炭工业科技计划(MTKJ2009-240)
引用文本：
沈学利,徐涛.基于改进型粒子群算法的PID 神经网络控制系统.计算机系统应用,2011,20(10):129-132
SHEN Xue-Li,XU Tao.PID Neural Network Control System Based on Improved Particle Swarm Optimization Algorithm.COMPUTER SYSTEMS APPLICATIONS,2011,20(10):129-132
沈学利,徐涛.基于改进型粒子群算法的PID 神经网络控制系统.计算机系统应用,2011,20(10):129-132
SHEN Xue-Li,XU Tao.PID Neural Network Control System Based on Improved Particle Swarm Optimization Algorithm.COMPUTER SYSTEMS APPLICATIONS,2011,20(10):129-132
