Disturbance suppression via robust MPC using prior disturbance data application to flight controller design for Gust Alleviation
Disturbance suppression via robust MPC using prior disturbance data application to flight controller design for Gust Alleviation
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DOI：
10.1109/cdc.2009.5399872
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发表时间：
2009-12
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影响因子：
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通讯作者：
Masayuki Sato;N. Yokoyama;A. Satoh
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文献类型：
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作者：
Masayuki Sato;N. Yokoyama;A. Satoh
本文利用含有测量误差的先验扰动数据，研究不确定对象系统的扰动抑制问题。我们使用模型预测控制（MPC）方案来解决最优控制输入设计问题，该方案利用先验测量的干扰数据。我们证明了如果植物系统的不确定性由控制输入处的有界但时不变的不确定延迟表示，那么我们只需要考虑有限多个植物模型而不是原始的不确定植物系统。此外，我们还表明，如果先前干扰数据中的测量误差表示为相对于某个常量不确定向量的仿射，其元素是有界的，那么我们只需要评估向量顶点处的测量误差。利用这些，我们提出了一个具有有限多条件的鲁棒MPC设计。最后，我们将提出的方法应用于抑制湍流驱动的垂直加速度的飞行控制器设计问题，即阵风缓解（GA）飞行控制器设计问题。
This paper addresses disturbance suppression problem for uncertain plant systems using prior disturbance data which contain some measurement errors. We tackle optimal control input design problem using Model Predictive Control (MPC) scheme in which a priori measured disturbance data are exploited. We show that if the uncertainties of the plant systems are expressed by bounded but time-invariant uncertain delays at the control input, then we only have to consider finitely many plant models instead of the original uncertain plant systems. Furthermore, we also show that if the measurement errors in prior disturbance data are expressed as affine with respect to some constant uncertain vector, whose elements are bounded, then we only have to evaluate the measurement errors at the vertices of the vector. Using these, we propose a robust MPC design with finitely many conditions for our addressed problem. Finally, we apply our proposed method to flight controller design problem for suppressing the vertical acceleration driven by turbulence, i.e. Gust Alleviation (GA) flight controller design problem.