基于神经网络PID的拖拉机空调温控系统优化设计

Optimal Design of Tractor Air Conditioning Temperature Control System Based on Neural Network PID

为了提高拖拉机空调温控系统的调节精度和效率,提升驾驶室内的环境舒适程度,将PID控制器引入到了拖拉机空调控制系统的设计上,采用温度误差反馈调节的方式,提高温控的精确性。在PID控制器的优化上采用了神经网络算法,通过神经网络训练和权值的修改,实现了PID控制器的3个参数的优化,进而提高了控制系统的效率和精度。为了验证神经网络算法对PID控制器的优化作用,以拖拉机的温控误差和调节时间为研究对象,对单独采用PID控制器和采用神经网络PID控制器时的控制结果进行了测试,结果表明:神经网络算法使PID控制器具有更快的响应速度和更高的控制精度。

In order to improve the regulation accuracy and efficiency of the tractor air conditioning temperature control system and improve the comfort level of the environment in the cab, it introduced the PID controller into the design of the tractor air conditioning control system. And it adopted the temperature error feedback regulation method to improve the accuracy of the temperature control. The neural network algorithm is adopted in the optimization of the PID controller, which is trained and weighted by the neural network. The modification of PID controller realizes the optimization of three parameters of PID controller, and then improves the efficiency and accuracy of control system. In order to verify the optimization effect of neural network algorithm on PID controller, the temperature control error and regulation time of tractor are taken as the research object. It tested the control results of PID controller and neural network PID controller. The test results show that neural network algorithm makes PID controller have faster response speed and higher control accuracy.