Abstract:

 A sliding mode controller based on self-learning disturbance observer (SLDO) is designed for a reusable launch vehicle (RLV). According to the singular perturbation theory, a RLV dynamic model is divided into the outer-loop and inner-loop subsystems. Since the model uncertainties and the disturbances vary with time and have unknown boundaries, combining with the type-2 neuro-fuzzy structure, feedback-error learning scheme and sliding mode control (SMC) theory, a novel online SLDO is presented. The multivariable supertwisting sliding mode controller driven by a SLDO is designed to track the re-entry trajectory precisely and convergent rapidly. Finally, by the simulation and analysis of the 6-degree-of-freedom model of RLV in the reentry phase, the effectiveness and the robustness of the integrated control scheme are verified.

Key words:  Reusable launch vehicle (RLV), Self-learning disturbance observer (SLDO), Sliding mode control (SMC), Reentry attitude track