串级液位控制系统是工业过程控制中最典型的系统，针对该系统具有不确定性和时变性的特点，首先在分析串级液位控制系统的结构和控制原理的基础上，采用实验建模的方法建立了系统的数学模型；然后充分利用 PID 结构简单、抗干扰能力强的特点以及神经网络具有自学习和自适应的特长，引入粒子群算法对网络权值进行优化，提出了一种基于改进粒子群算法的神经网络 PID 控制器，既克服了 BP神经网络收敛速度慢，容易陷入局部极小值的缺点，也克服了粒子群算法容易陷入局部最优的缺点；最后在 MATLAB环境下进行串级液位系统的仿真试验对系统的性能进行分析，实验结果表明，该控制算法具有良好的实时性、鲁棒性，抗干扰能力强，显著提高了系统的性能指标。%String loop liquid control system is the typical system in industry process control.The system has the characteristics of uncer-tainty and time-variable.Based on analysis of the structure and control principle of string loop liquid control system,this paper has built systemic mathematical model by modeling.Then,introduce particle swarm algorithm to optimize the network's weight combined with the characteristics of PID simple structure,strong anti-interference ability and the advantage of the neural network's self-learning and self-a-daptive.Advance a kind neural network PID controller based on improved particle swarm algorithm.The algorithm conquered slow conver-gence speed and easily getting into local dinky value of BP neural network,and easily getting into local optimization of particle swarm.Ana-lyze the system's performance by string loop liquid control system's experiment in MATLAB.The result indicated that the control system had good realtime,robustness and strong anti-interference ability.The capability of the system is improved notably.
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