Punctuality Algorithm Based on BP Neural Network PID Control

Abstract

In the modern information society, high-precision clocks are particularly important in the fields of electric power, communications, aviation, and finance, and have very strict objective requirements in terms of frequency accuracy. Currently, the technology of using GPS satellite clock sources to synchronize local clocks has become one of the mainstream methods for generating high-precision clocks at home and abroad. The core idea of this technology is to use the satellite clock to tame the local clock. Due to the development and application of 5G, the accuracy of the system's punctuality have higher requirements, Through analysis, it is found that the combination of BP neural network and PID control can be used to optimize the control of the constant temperature crystal oscillator and improve the precision of punctuality. Finally, the simulation results show that the method has a significant effect in improving the accuracy of punctuality.

Research on intelligent control of automobile active suspension based on BP neural control model

“…By constantly adjusting the weight and bias in the network, the algorithm enables the network to learn and adapt to the characteristics of the input data, so as to realize the modeling and prediction of complex problems. Figure 1 below is a diagram of BP neural network [8] . The S function is used to excite the input of the hidden neuron to obtain the output X of the hidden neuron…”

Improved PID Controller Based on BP Neural Network

“…During the operation of the controlled object, the real-time setting of the control parameters Kp, Ki, and Kd is very important. Based on the combination of the PID controller and BP neural network [4] , the controller structure is simplified, and the self-learning optimization of controller parameters is realized through the neural network system, thus improving the performance of the controller [5] .…”