Multi-step predictive inverse control based on neural networks
神经网络非线性多步预测逆控制方法研究*

This paper developed a neural-network inverse control scheme for nonlinear MIMO discrete systems based on multi-step prediction. Used a predictive model for predicting dynamic characteristics of the system. A neural network with time-delay modules acted as the inverse controller, which was trained with predictive optimization algorithm to implement the inverse system. Used another neural network to model the prediction error to compensate for the predictive output. Simulation results illustrate that the control strategy has a favorable decouple and dynamic tracking performance to nonlinear systems.