Neuro-adaptive Predefined-time Control for Mars Entry Vehicle under Uncertainties and Output Constraints

This paper concentrates on the neuro-adaptive predefined-time tracking control problem for Mars entry vehicle subject to uncertainties and output constraints. First, an improved predefined-time stable (PTS) criterion is constructed to enhance the flexibility in control design procedure, and the universal barrier function (UBF) is employed to handle the asymmetrical output constraints. Then, by blending PTS criterion and UBF technique into sliding mode control design, an adaptive predefined-time nonsingular terminal sliding mode control (PNTSMC) scheme is developed. Under the resultant control scheme, fast convergence, strong robustness, and the prescribed constraints requirements are guaranteed, which are deemed grateful in practical aerospace applications. Subsequently, the neural networks (NNs) are utilized to approximate the lumped uncertainties, and an adaptive law is incorporated into controller design such that all closed-loop signals ensure the practically predefined-time convergence determined by the user-selected parameter. Finally, the validity of developed approach is confirmed by simulation results.