Adaptive-gain multivariable super-twisting sliding mode control for reentry RLV with torque perturbation

Reusable launch vehicle (RLV) should be under control in the presence of model uncertainty and external disturbance, which is considered as torque perturbation in this paper during the reentry phase. Such a challenge imposes tight requirements to the enhanced robustness and accuracy of the vehicle autopilot. The key of this paper is to propose an adaptive-gain multivariable super-twisting sliding mode controller when considering that the bounds of uncertainty and perturbation are not known. The important features of the controller are that the adaptation algorithm can achieve non-overestimating values of the control gains and the multivariable super-twisting sliding mode approach can obtain a more elegant solution in finite time. According to the multiple-time scale features, the dynamics of RLV attitude motion are divided into outerloop subsystem and inner-loop subsystem. On this basis, the controllers are designed respectively to ensure the finite-time reentry attitude tracking. In addition, a proof of the finite-time convergence for the overall system is derived using the Lyapunov function technique and multiple-time scale characteristic. Finally, simulation results of six degree-of-freedom RLV are provided to verify the effectiveness and robustness of the proposed controller in tracking the guidance commands as well as achieving a safe and stable reentry flight. Copyright (C) 2016 John Wiley & Sons, Ltd.