Robust Control and Filtering for Airships with Wind Disturbance Estimation

This paper presents a design methodology for the automatic control system of an airship, accounting for atmospheric disturbances and parametric modeling uncertainties. The derived design model is a linear stochastic system with multiplicative noise incorporating both the airship’s uncertain dynamics and the wind model. First, an H_∞ state feedback control law is derived for the stochastic system to ensure robust stability and trajectory tracking performance. Subsequently, a robust Kalman filter is designed to estimate the turbulence model states based on available measurements. It is demonstrated that the optimal gain of this robust filter depends on the solution to a coupled system of specific Riccati and Lyapunov equations. Numerical results highlight a significant improvement in robustness and tracking performance when the control law incorporates wind gust velocity estimation.