The tightly coupled, highly nonlinear, and notoriously uncertain nature of hypersonic vehicle dynamics brings a great challenge to the control system design. In this paper, an integrated controller based on Differential flatness theory and L1 adaptive theory is designed, and a nonlinear disturbance observer is added to solve the problem of model uncertainty. Differential flatness is applied to the outer loop to linearize the nonlinear model, and L1 adaptive control is applied to the inner loop to stabilize the attitude. The combination realizes the complementarity of their shortcomings. It can not only retain the advantages of L1 adaptive controller, but also avoid wide range of state changes and makes it easy to design parameters satisfying global convergence. The computational order of differential flatness is also reduced and the design of nonlinear disturbance observer becomes feasible. Simulation results for the hypersonic vehicle are presented to demonstrate the effectiveness and robustness of the proposed control scheme.
A Fuzzy Model Predictive Control Based Upon Adaptive Neural Network Disturbance Observer for a Constrained Hypersonic Vehicle