Modeling and Optimization Control for Aircraft AC Generator Brushless Excitation System

The paper analyzes aircraft Alternating-Current (AC) generator brushless excitation system structure and work principle. The simulation model of aircraft brushless excitation system is implemented in MATLAB/SIMULINK accord- ing to the differential equations for each element. Due to the strong nonlinearity and time-varying of three-stage aircraft generator excitation system, the conventional PID controller has slow response speed, long adjustment time and low steady state accuracy. It is unable to meet the requirements of More Electric Aircraft (MEA) or All Electric Aircraft (AEA). In order to solve this problem, the adaptive excitation control scheme of radical basis function (RBF) neural net- work and conventional PID is proposed which is optimized by adaptive particle swarm optimization (PSO). The mutual coupling parameters which are PID parameters Kp, Ki, Kd and RBF parameters b, c, , are optimized based on parti- cle swarm during control time. The simulation results show that the optimized RBF-PID excitation controller has the characteristics of quick response speed, short adjusting time and high precision. The system has good robustness, real- time, high tracking accuracy and stronger adaptive ability.