论文部分内容阅读
构建了基于PLC和组态技术的分布式监控系统的硬件平台,设计开发了下位机PLC的监控程序和基于WinCC组态环境下上位机的监测程序。针对矿井通风系统具有惯性大、时滞大、非线性等特点,提出了基于BP神经网络的PID控制方案,设计了神经网络自适应PID控制器,仿真结果表明,该方法可提高控制系统的实时性、适应性和鲁棒性。对提高矿井通风机运行的安全性和控制的准确性,保证煤矿安全高效生产具有重要的现实意义。
The hardware platform of distributed monitoring system based on PLC and configuration technology was constructed. The monitoring program of lower computer and the monitoring program of upper computer based on WinCC configuration environment were designed and developed. Aimed at the characteristics of mine ventilation system such as large inertia, large time delay and nonlinearity, a PID control scheme based on BP neural network is proposed and a neural network adaptive PID controller is designed. The simulation results show that this method can improve the real-time Sexuality, adaptability and robustness. It is of great practical significance to improve the safety of mine ventilator operation and control accuracy and to ensure the safe and efficient production of coal mines.