Robust controller design based on hankel norm and gap metrics for BTT flight vehicle

Dynamic uncertainties and flight environment uncertainties are important factors that affect attitude control performance of Bank-to-Turn vehicle. Low order robust controller design method under these uncertainties is presented. A dual-loop control architecture using state-feedback and μ synthesis combined with genetic algorithm is presented. The feedback parameters and the weight functions of μ controller are optimized by using the genetic algorithm. A controller reduction method based on Hankel norm and gap metrics is proposed to reduce the order and complexity of the robust controller. A lower order robust controller guaranteeing the stability and tracking performance of the close-loop system is obtained. The simulation results show the design method is effective. The design procedure and analysis show that this method is also effective in the tracking system with model uncertainties.