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针对高超声速飞行器纵向模型,考虑参数摄动、未建模动态和外界干扰等各种不确定性因素的综合影响,提出了一种基于非线性增益的递归滑模动态面控制方案。该方案通过非线性增益函数调节高超声速飞行器姿态控制精度与控制增益之间的矛盾,利用神经网络逼近飞行器气动参数不确定性和未知外界干扰,进一步通过设计递归滑模动态面控制器提高系统的控制精度。仿真结果表明,所提控制方案不仅提高了飞行器的控制精度,而且对模型不确定性和外界干扰具有较强的鲁棒性。
Aiming at the longitudinal model of hypersonic vehicle, considering the combined influence of uncertainties such as parameter perturbation, unmodeled dynamics and external disturbances, a nonlinear recursive sliding mode dynamic surface control scheme is proposed. The scheme adjusts the contradiction between attitude control precision and control gain of hypersonic vehicles by using nonlinear gain function. The neural network is used to approximate the uncertainty of aerodynamic parameters and the unknown external disturbance. The design of recursive sliding mode dynamic surface controller control precision. Simulation results show that the proposed control scheme not only improves the control accuracy of the aircraft, but also has strong robustness to model uncertainty and external disturbances.