【摘要】 提出在航空关节轴承试验机加载控制系统中应用极限学习机(ELM)对电液力PID控制参数进行在线调节的方法。解决了BP神经网络梯度下降法速度太慢导致在伺服系统中PID控制实时性太差的问题。实验结果表明,该方法泛化性能好、学习速度快、模型精度高,具有很强的实践指导意义。更多还原

【Abstract】 A method of electric hydraulic PID control parameters online adjust approach is proposed by using the extreme learning machine( ELM) in loading control system of aviation joint bearing testing machine. The poor realtime performance of PID control in servo system is solved when the BP neural network gradient descent method is used. The experimental results show that this method has a good generalization performance,learning speed and model precision,and has a strong practical guiding significance.更多还原