Stability analysis of intelligent English translation system based on model predictive control algorithm

Abstract

English translation systems often require manual input to convert speech into text document mode, which leads to poor translation results. In order to improve the intelligence of the intelligent English translation system, based on the machine learning algorithm, this paper constructs an intelligent English translation system based on the model predictive control algorithm, and combines the self-triggering MPC with the robust control to propose a corresponding control solution. That is, a robust self-triggering MPC method is proposed for linear systems with constraints. Moreover, this paper studies the stability and robustness of MPC in continuous time systems and describes the interfaces to be used in the system and the performance requirements of the system. In addition, this paper analyzes and describes the feasibility of the system development plan. Finally, this paper designs experiments to analyze the model performance from the system translation accuracy rate, system login security and system stability. The research results show that the model constructed in this paper has certain practical effects.