Optimized Adhesion Control of Locomotive Airbrake Based on GSA-RNN

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.