基于动态补偿神经网络误差修正的广义预测控制

Generalized predictive control based on error correction using dynamically compensating neural network

本文采用权值可在线调整的动态补偿神经网络(动态BP网络)对模型预测误差进行拟合,从而显著提高了基于线性模型的非线性广义预测(GPC)的预测精度,增强了算法的鲁棒性。

a Generalized predictive control algorithm based on error correction using dynamically compensating neural network is proposed to approximate the modeling error. So it improves the predictive accuracy of GPC based on linear model and buildups systems robustness. The simulation results show the algorithm is effective for nonlinear system.