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Robust adaptive backstepping sliding mode control of near space vehicle via self-organizing hermite-polynomial-based neural network controller

机译:基于自组织基于Hermite多项式的神经网络控制器的鲁棒自适应反推滑模控制

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摘要

A novel sliding mode method is proposed for near space vehicles with unknown external disturbance, parameter uncertainties and modeling error. The self-organizing hermite-polynomial-based neural network controller is presented to estimate the unknown compound disturbance. Based on it, we propose backstepping sliding mode strategy which may reduce the initial gains and the stability is proved by Lyapunov function. The simulation results demonstrate the effectiveness of the scheme.
机译:针对未知外部干扰,参数不确定性和建模误差的近太空飞行器,提出了一种新的滑模方法。提出了一种基于自组织埃尔米特多项式的神经网络控制器,用于估计未知的复合扰动。在此基础上,提出了可以减小初始增益的后推滑模策略,并通过Lyapunov函数证明了算法的稳定性。仿真结果证明了该方案的有效性。

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