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Robust model predictive control based on polytopic LPV model for hypersonic vehicles

机译:基于多目标LPV模型的高超声速飞行器鲁棒模型预测控制

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Considering the air-breathing hypersonic vehicle (AHV) system with strong nonlinearity and external disturbance, an off-line robust model predictive controller (RMPC) is presented based on the polytopic LPV model under the effects of disturbances. Firstly, Jacobian linearization and tensor-product modeling method are used to approximately transform the nonlinear AHV system into a polytopic LPV model, which provides the condition to establish the RMPC controller by linear matrix inequality (LMI). Secondly, the application of norm-bounding technology makes the errors between real-time states with disturbance and the reference setpoint states restricted into an invariant ellipsoid. Simulation has demonstrated the effectiveness of the proposed approach.
机译:考虑到具有高非线性和外部干扰的呼吸高超音速飞行器(AHV)系统,在干扰的影响下,基于多目标LPV模型提出了一种离线鲁棒模型预测控制器(RMPC)。首先,利用雅可比线性化和张量积建模方法将非线性AHV系统近似转换为多目标LPV模型,为通过线性矩阵不等式(LMI)建立RMPC控制器提供了条件。其次,范数有界技术的应用使得受干扰的实时状态与参考设定点状态之间的误差被限制为不变的椭球。仿真证明了该方法的有效性。

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