Terminal sliding mode attitude tracking control for unmanned vehicle with predefined-time stability

In this paper, we proposed a predefined-time terminal sliding mode approach for attitude tracking control of unmanned aerial vehicle (UAV). In order to obtain the high convergence speed and steady-state performance controller, the modified non-singular terminal sliding mode control (TSMC) we adopted can switch sliding mode surfaces under different conditions. The system stability is achieved within a predefined time, which can be set by modifying the explicit parameters in advance. Due to the existence of model uncertainties and unknown external disturbances, an adaptive neural network-based approach is applied to compensate the error between the actual and nominal model without requiring any prior knowledge of the disturbances. Several comparative studies are carried out between the proposed approach and other predefined-time techniques in previous work, and simulation results and experimental results are presented to validate the correctness of analysis and superiority of the proposed control scheme.