An Novel Predictive Control Method Based on Regularized Echo State Network and Improved Sparrow Search Optimization Algorithm

In this paper, combining the advantages of regularized echo state network and improved sparrow search optimization, a novel prediction control method is proposed. Compared with the traditional recurrent neural network, the prediction model based the regularized echo state network has the advantages of simple training and less computational burden. Through using the reverse learning strategy and the Levy flight strategy, the sparrow optimization algorithm is improved for optimizing the reservoir parameters of the regularized echo state network. Finally, for the predictive control of the buck converter, the simulation experiments demonstrate the effectiveness of the proposed predictive control method.