Wavelet neural network prediction algorithm based on improved implicit generalized predictive control
In this paper, the wavelet neural network (WNN) is used to predict the delay period, and combined with implicit generalized predictive control to delay compensation for the networked control system. The random delay in the networked control system (NCS) leads to the performance degradation of the system, in order to solve this problem, a wavelet neural network is used to establish the prediction model of the random delay in the NCS, and the algorithm is used to predict Delay period combined with implicit generalized predictive control algorithm to compensate for the NCS random delay. The simulation results show that the wavelet neural network algorithm has higher prediction accuracy for the random delay period, and at the same time makes the network system have good signal tracking ability and improves the control performance of the traditional generalized predictive control algorithm.