【摘要】 将神经网络与传统的PID控制相结合,构成神经网络自学习PID控制,用神经网络在线整定PID控制器的比例、积分及微分三个参数,使被控对象跟踪理想参考模型的输出。该系统具有自学习能力,能适用于非线性、时变的被控对象。将神经网络自学习PID控制方法用于航空发动机全包线控制以及蜕化发动机的控制,进行了数字仿真,验证了该方法的有效性。更多还原

【Abstract】 A self-learning PID controller based on neural networks and conventional PID control was developed.The parameters of PID controller are tuned on-line with the neural networks to make the output of the controlled plant follow the desired output of a reference model.The resulting control system is capable of self-learning and can be used for controlling nonlinear and time-varying plant.The proposed method is applied to aeroengine control.Digital simulation results show that the self-learning PID control proposed is effective to control nominal and deteriorated aeroengine in full envelope.更多还原