Stochastic approach to robust flight control design using hierarchy-structured dynamic inversion

The stochastic approach to robust flight control design using hierarchy-structured dynamic inversion (HSDI) was examined. Intensive robustness evaluation by root sum square (RSS) and Monte Carlo simulation (MCS) was performed using an elaborate nonlinear model of a subscale reentry vehicle, which revealed the HSDI autoland controller to be as robust as the baseline linear robust controller. Touchdown robustness was finally enhanced by a stochastic optimization scheme using the downhill simplex method combined with MCS evaluation. The optimization results showed that the HSDI autoland controller realized better touchdown robustness due to the simultaneous tuning of its guidance and control parameters. An HSDI-based flight control design methodology reduces design cost due to its easy-to-tune control structure and has sufficient robustness for practical applications in industry.