A novel modeling approach for the magnetorheological brake system based on improved LSTM

Abstract

Abstract In order to model the magnetorheological brake system under long-term operation and different working conditions, a novel performance prediction approach based on an improved long short term memory (LSTM) model is proposed to solve this problem. The framework of the proposed approach is presented, and an improved sparrow search algorithm is designed to optimize the hyperparameters of LSTM. Moreover, the proposed prediction approach based on improved LSTM is designed and the flowchart of this approach is shown. In addition, the first simulation example was carried out to demonstrate the effectiveness of the proposed model compared with the artificial neural network model and the conventional geometric model. Finally, the other simulation example was designed to exhibit the superior performance of the proposed algorithm compared with other algorithms.