モデル予測制御を用いた突風軽減制御：事前乱気流情報および機体運動状態量の観測誤差に対するロバスト性

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  • Gust Alleviation Control Using Model Predictive Control -Robustness against Measurement Errors in Prior Turbulence Data and Current State Variables for Aircraft Motions-
  • モデル ヨソク セイギョ オ モチイタ トップウ ケイゲン セイギョ ジゼン ラン キリュウ ジョウホウ オヨビ キタイ ウンドウ ジョウタイリョウ ノ カンソク ゴサ ニ タイスル ロバストセイ
  • Gust Alleviation Control Using Model Predictive Control —Robustness against Measurement Errors in Prior Turbulence Data and Current State Variables for Aircraft Motions—

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This paper addresses the design problem of flight controllers for suppressing aircraft motions due to turbulences, i.e. design problem of Gust Alleviation (GA) flight controllers. As LIght Detection And Ranging (LIDAR) system which can detect even Clear Air Turbulences (CAT) has recently been developed, flight controllers which exploit the prior turbulence data that are obtained using LIDAR system have been desired. In this note, we extend our previously proposed method to the even realistic situations in which there exist plant uncertainties and the measurement errors in current state variables for aircraft motions as well as in the prior turbulence data. We successfully propose a design method of GA flight controllers for our problem using Model Predictive Control (MPC). Numerical simulation results which demonstrate the applicability of our proposed method for GA feasibility study are included.

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