Adaptive Dual-Loop Disturbance Observer-Based Robust Model Predictive Tracking Control for Autonomous Hypersonic Vehicles

To solve the attitude trajectory tracking problem for hypersonic vehicles in the presence of system constraints and unknown disturbances, this paper designed a nonlinear robust model predictive control (RMPC) scheme, which can produce near-optimal tracking commands. Unlike the existing designs, the proposed scheme is less conservative and successfully prioritizes the solution optimality. The established RMPC follows a dualloop structure. Specifically, in the outer feedback loop, the reference attitude angle profiles are optimally tracked, while in the inner feedback loop, the control moment commands are produced by optimally tracking the desired angular rate trajectories. Besides, an adaptive disturbance observer (ADO) is designed and embedded in the inner and outer RMPC controllers to alleviate the negative effects caused by unknown external disturbances. The recursive feasibility of the optimization process, together with the input-to-state stability of the proposed RMPC, is theoretically guaranteed by introducing a tightened control constraint and terminal region. The derived property reveals that our proposal can steer the tracking error within a small region of convergence. Finally, the effectiveness of the proposed scheme is demonstrated by performing simulation studies.