A robust adaptive nonlinear fault-tolerant controller via norm estimation for reusable launch vehicles

• DSC approach is used to design fault-free controller.
• Compensation controller is constructed for loss fault of actuator effectiveness.
• Fuzzy logic system is utilized to approximate the lumped uncertainties.
• Computation is reduced by minimal learning parameter strategy via norm estimation.
• Maximum eigenvalue of actuator efficiency loss factors is estimated online.

In this paper, a reusable launch vehicle (RLV) attitude control problem with actuator faults is addressed via the robust adaptive nonlinear fault-tolerant control (FTC) with norm estimation. Firstly, the accurate tracking task of attitude angles in the presence of parameter uncertainties and external disturbances is considered. A fault-free controller is proposed using dynamic surface control (DSC) combined with fuzzy adaptive approach. Furthermore, the minimal learning parameter strategy via norm estimation technique is introduced to reduce the multi-parameter adaptive computation burden of fuzzy approximation of the lump uncertainties. Secondly, a compensation controller is designed to handle the partial loss fault of actuator effectiveness. The unknown maximum eigenvalue of actuator efficiency loss factors is estimated online. Moreover, stability analysis guarantees that all signals of the closed-loop control system are semi-global uniformly ultimately bounded. Finally, illustrative simulations show the effectiveness of the proposed method.