基于BP网络的PID自整定算法在水产养殖监控系统中的应用

PID self-adjusted arithmetic based on Back Propagation using in aquiculture

传统的PID控制的参数不易调整。在系统模型不确定的情况下,使比例因子、积分因子、微分因子的调节成为很困难的事。而神经网络具有很好的自调节作用,因此本文引入神经网络来对控制参数进行在线自整定,实现参数的自动优化。并将此控制方法成功的应用于水产养殖工程中的溶解氧控制中。在现场应用中,该系统对养殖水体溶解氧含量进行了自动监测和控制,其性能稳定。

It is hard to find parameters of proportional, integral and derivative in tradition PID arithmetic. When the model of system is unknown, it becomes harder. Because NN can adjust himself through studying, so here NN was used to search for the optimum parameters of PID. And be used in aquiculture to control Dissolved -Oxygen in the water. In locale test, it works well in controlling Dissolved-Oxygen, and this system improves the density of fish.