中文说明：多变量输入、输出、多干扰、非线性和强耦合的复杂系统控制是一个比较困难的问题，常用的控制器可能因为多变量耦合问题难以控制系统。PID神经元网络是一种多层前向神经元网络，它的各层神经元个数、连接方式、连接权值是按照PID控制规律的已有原则和经验确定的，是一种动态的符合控制系统的前向网络。但是由于PID网络初始权值随机取值的原因，每次控制的效果都有所差别，个别情况下控制效果还比较差。本案例研究了基于PID神经元的多变量耦合系统控制，并用PSO算法来优化控制器以取得更好的控制效果。
English Description：
Multi-variable input, output, and much other, strongly coupled complex systems and nonlinear control is a very difficult problem, controllers for Multivariable coupling problems common to control systems. Is a multilayer feedforward neural network PID neural networks, its nerve cell number, connection, connection weights is based on PID control strategy has determined principles and experience, is a dynamic line with control systems networks. But due to the random initial weights PID network value reasons, each effect are somewhat different, individual case-control effect is still relatively poor. This case study is based on PID neural control of multivariable coupling systems using PSO algorithm for optimized controller to achieve better results.