Stochastic Robust Control of Hypersonic Vehicle Based on Quasi-random Sampling

In this paper, we propose a new approach to design stochastic robust controller for hypersonic vehicles. By replacing pseudo-random sequence used in classic Monte Carlo Estimation (MCE) with quasi-random sequence, which is also known as Low-Discrepancy Sequence (LDS), it costs less time to generate an ideal robust controller. The samples drawn using quasi-random sequences can evenly cover the entire sampling space, reflect the real situations better than random sampling. Therefore, we can ensure better tracking accuracy in low-risk situations at high-probability, while avoiding instability in high-risk situations at low-probability. We verify the effectiveness of this method versus traditional stochastic robust controller design via simulations, and the LDS-based controller shows better performance in uncertain environments.