Adaptive neural observer-based backstepping fault tolerant control for near space vehicle under control effector damage

In this study, a theoretical framework for reconfigurable flight control is developed and applied to near space vehicle (NSV) attitude dynamics. First, NSV reentry mode is described. Second, an adaptive neural network observer is proposed, which ensures asymptotic convergence of the state observer error to zero under control effector damage and uncertainty. Next, a reconfigurable command-filter backstepping controller is designed based on the adaptive neural network observer. The authors focus is on the accommodation of the control effector damage, uncertainty and resulting disturbances. It is shown that the presented new control design results in asymptotic convergence of the attitude tracking error to zero. Finally, simulation results are given to demonstrate the effectiveness and potential of the proposed fault tolerant control scheme.