Optimized Adhesion Control of Locomotive Airbrake Based on GSA-RNN

摘要

Locomotive air brake intelligent optimization adhesion control algorithm based on GSA-RNN was put forward in order to solve the problem of adhesion performance optimization during the process of locomotive air braking. A adhesion controller has been designed based on RNN and the adhesive force and brake cylinder pressure are used as performance index, a algorithm of dynamic multi group of gravitational search is used to optimized the controller's parameters. The simulation model of locomotive air braking adhesion control is built and the optimized adhesion control under different rail surface condition is simulated on the platform of Matlab/Simulink. The results show that the put forward locomotive air brake intelligent optimization adhesion control strategies based on GSA-RNN can effectively guarantee the quality of optimized adhesion control and get optimal adhesion utilization.