Disturbance Observer-Based Adaptive Predefined-Time Attitude Control for Tiltrotor UAVs With Actuator Faults

Ensuring predefined-time convergence, strong robustness, and global adaptability is of great significance for improving the control performance and operation reliability of tiltrotor unmanned aerial vehicles with nonlinear dynamics, external disturbances, and actuator faults. To address these challenges, this study explores a disturbance observer-based adaptive predefined-time attitude control strategy. Compared to existing predefined-time systems, an improved predefined-time system is first proposed, offering both faster convergence speed and tunable convergence time. Building on this system, an adaptive predefined-time disturbance observer is designed to estimate unknown disturbances without requiring stringent assumptions such as continuous differentiability, negligible variation, or known upper bounds. Moreover, the designed observer achieves chattering-free disturbance estimation and updates its gain online, thereby improving estimation quality and adaptability across diverse operating scenarios. Subsequently, an adaptive command filter and an adaptive filter error compensation system are introduced to address the “explosion of complexity” problem arising from the repeated differentiation of virtual control inputs, and compensate for the filtering errors, respectively. This design helps to reduce computational complexity and enhance control precision. To further address system nonlinearities and actuator bias faults, a low-computational neural network is developed that updates only a single virtual parameter instead of a vector-valued function, significantly lowering the computational burden. In particular, an adaptive gain-based mechanism is integrated into the controller to estimate the unknown actuator effectiveness factor. Finally, Lyapunov-based stability analysis proves that the control error converges to a bounded region within the predefined time, and extensive comparative results are presented to validate the effectiveness and superiority of the developed control strategy.