磁轴承BP神经网络PID控制算法研究

Research on BP Neural Network PID Control Algorithm for Magnetic Bearing

针对传统PID控制算法难以解决磁悬浮系统非线性的问题,设计一种BP神经网络PID控制算法。通过仿真分析与试验研究,比较普通PID控制算法与BP神经网络PID控制算法对磁悬浮系统的实际控制效果。研究结果表明:BP神经网络PID控制算法可以改善磁悬浮系统的静动态性能,并使系统具有自学习、自适应的能力。

To overcome the difficulty in solving the problem of nonlinearity of magnetic levitation system by the traditional PID control algorithm,a BP neural network PID control algorithm is designed.Through simulation analysis and experimental research,the actual control effect of the ordinary PID control algorithm and the BP neural network PID control algorithm on the maglev system are compared.The research results show that the BP neural network PID control algorithm can improve the static and dynamic performance of the maglev system and enables the system to have self-learning and self-adaptive abilities.