基于神经网络的磁悬浮球自适应控制器

建立了磁悬浮球系统的数学模型，讨论了系统的刚度阻尼和控制系统之间的关系。利用神经网络的学习功能在传统比例积分微分（PID）控制器的基础上构建了一种自适应PID控制器。用于磁悬浮球控制系统。实验结果表明，控制器结构简单，易于工程实现，可以实现磁悬浮球的稳定悬浮，并且系统具有快速响应性和良好的抗干扰性。

PID controller of magnetic levitation ball based on neural network

The mathematical model of the magnetic levitation ball system was built,and the relation between the stiffness damping of system and the control system was discussed,the design of adaptive PID controller that applied learning ability of the neural network based on the traditional PID control was introduced,and it was used in the magnetic levitation ball control system.The experiments show that,the structure was simple and was realized easily in industry application,the ball can be suspended stably,the system has response rapidly and good performance of anti-disturbance.