Model predictive trajectory tracking of a reentry hypersonic vehicle based on convex optimization

The guidance and control problem of hypersonic vehicles is challenging due to the strong nonlinearity and big uncertainty of the system and multiple constraints during the flight, such as heat and dynamic pressure. Trajectory-tracking problem of a reentry hypersonic vehicle is studied in this paper and a model predictive control (MPC) strategy is proposed. In order to improve the speed of MPC, the optimization problem at each time step is transformed into a convex form and accordingly convex optimization is used to obtain the control action. The resulting model predictive control method is able to take into consideration the actuator constraints and requirements on heat and dynamic pressure, which set it aside form most classical methods. Errors caused by model uncertainty are revised according to real-time information of the system. The newly developed convex optimization solver CVXGEN is utilized successfully in the method evaluation. Providing solve times in milliseconds, which makes real-time implementations of the MPC controller feasible. Simulation results show that the proposed trajectory tracking strategy can realize good performance with the existence of aerodynamic uncertainty. All the constraints are fulfilled even when the given nominal trajectory has violations.