JP6466398B2 - コンパクトな空力熱モデルのリアルタイム線形化を用いた状態推定器 - Google Patents
コンパクトな空力熱モデルのリアルタイム線形化を用いた状態推定器 Download PDFInfo
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Description
Claims (20)
- 制御される装置(130)の制御面を位置決めするアクチュエータ(124)と、
モデル出力の関数として前記アクチュエータ(124)に指示する制御法則(111)と、
前記モデル出力を生成するモデル処理装置(110)と、
を備え、
前記モデル処理装置(110)は、
モデル入力ベクトルを処理し、モデル動作モードを設定する入力オブジェクト(220)と、
前記モデル動作モードに基づいて、オープンループモデル(410)に入力される前記モデル処理装置(110)の動的状態を設定する設定状態モジュール(420)であって、前記オープンループモデル(410)が、前記動的状態および前記モデル入力ベクトルの関数として現在の状態の導関数、ソルバエラーベクトル、および合成パラメータを生成し、前記現在の状態の導関数およびソルバエラーベクトルへの制約が、一連のサイクル合成モジュールに基づき、前記一連のサイクル合成モジュールの各部が、前記制御される装置(130)のサイクルの構成要素をモデル化し、一連のプログラムを備え、前記一連のプログラムが、前記構成要素の挙動に関わる物理法則の数学的抽象化に基づいている、設定状態モジュール(420)と、
前の状態、前記現在の状態の導関数、前記ソルバエラーベクトル、および前記合成パラメータのうちの少なくとも1つに基づいて前記モデルの推定状態を決定する推定状態モジュール(440)であって、前記モデルの推定状態を決定するために、オンライン線形化およびゲイン算出(441)を用いて推定器ゲインを決定する、推定状態モジュール(440)と、
前記モデル出力を決定するために前記モデルの少なくとも前記合成パラメータを処理する出力オブジェクト(240)と、
を備える、制御システム(100)。 - 前記オンライン線形化およびゲイン算出(441)は、現在の状態、前記モデル入力ベクトル、前記モデル出力、および前記合成パラメータに基づく偏導関数を取得すること(443)を含むことを特徴とする請求項1に記載の制御システム(100)。
- 前記偏導関数は、ヤコビ行列であることを特徴とする請求項2に記載の制御システム(100)。
- 前記オンライン線形化およびゲイン算出(441)は、前記偏導関数を用いてゲイン設計(445)のための線形システムを構築することをさらに含むことを特徴とする請求項2に記載の制御システム(100)。
- 前記オンライン線形化およびゲイン算出(441)は、ゲイン設計のための前記線形システムに基づいて前記推定器ゲイン(447)を決定することをさらに含むことを特徴とする請求項4に記載の制御システム(100)。
- 前記推定器ゲインは、エラーベクトルの最小化に用いられることを特徴とする請求項1に記載の制御システム(100)。
- 前記推定状態モジュール(440)は、前記前の状態および前記現在の状態の導関数に基づいて前記モデルの推定状態を決定するために数値積分(448)を用いることを特徴とする請求項6に記載の制御システム(100)。
- 前記制御される装置(130)は、ガスタービンエンジンであることを特徴とする請求項1に記載の制御システム(100)。
- 前記1つまたは複数のサイクル合成モジュールが、前記ガスタービンエンジンの熱力学的サイクルの構成要素に関連する1つまたは複数の物理的性質の数学的抽象化に基づくことを特徴とする請求項8に記載の制御システム(100)。
- モデル処理装置(110)を用いてモデル出力を生成するステップと、
制御法則を用いて、前記モデル出力の関数として、制御される装置(130)に関連するアクチュエータ(124)に指示するステップと、
前記アクチュエータ(124)を用いて、前記制御される装置(130)の制御面を位置決めするステップと、
を含む、制御される装置(130)の制御方法において、
前記モデル処理装置(110)は、
モデル入力ベクトルを処理し、モデル動作モードを設定する入力オブジェクト(220)と、
前記モデル動作モードに基づいて、オープンループモデル(410)に入力される前記モデル処理装置(110)の動的状態を設定する設定状態モジュール(420)であって、前記オープンループモデル(410)が、前記動的状態および前記モデル入力ベクトルの関数として現在の状態の導関数、ソルバエラーベクトル、および合成パラメータを生成し、前記現在の状態の導関数およびソルバエラーベクトルへの制約が、一連のサイクル合成モジュールに基づき、前記一連のサイクル合成モジュールの各部が、前記制御される装置(130)のサイクルの構成要素をモデル化し、一連のプログラムを備え、前記一連のプログラムが、前記構成要素の挙動に関わる物理法則の数学的抽象化に基づいている、設定状態モジュール(420)と、
前の状態、前記現在の状態の導関数、前記ソルバエラーベクトル、および前記合成パラメータのうちの少なくとも1つに基づいて前記モデルの推定状態を決定する推定状態モジュール(440)であって、前記モデルの推定状態を決定するために、オンライン線形化およびゲイン算出(441)を用いて推定器ゲインを決定する、推定状態モジュール(440)と、
前記モデル出力を決定するために前記モデルの少なくとも前記合成パラメータを処理する出力オブジェクト(240)と、
を備える、制御される装置(130)の制御方法。 - 前記オンライン線形化およびゲイン算出(441)は、現在の状態、前記モデル入力ベクトル、前記モデル出力、および前記合成パラメータに基づく偏導関数を取得すること(443)を含むことを特徴とする請求項10に記載の制御される装置(130)の制御方法。
- 前記オンライン線形化およびゲイン算出(441)は、前記偏導関数を用いてゲイン設計のための線形システムを構築すること(445)をさらに含むことを特徴とする請求項11に記載の制御される装置(130)の制御方法。
- 前記オンライン線形化およびゲイン算出(441)は、ゲイン設計のための前記線形システムに基づいて前記推定器ゲインを決定すること(447)をさらに含むことを特徴とする請求項12に記載の制御される装置(130)の制御方法。
- 前記推定器ゲインは、エラーベクトルの最小化に用いられることを特徴とする請求項10に記載の制御される装置(130)の制御方法。
- 前記推定状態モジュール(440)は、前記前の状態および前記現在の状態の導関数に基づいて前記モデルの推定状態を決定するために数値積分(448)を用いることを特徴とする請求項14に記載の制御される装置(130)の制御方法。
- ファンと、
前記ファンの下流の圧縮機区画と、
前記圧縮機区画の下流の燃焼器区画と、
前記燃焼器区画の下流のタービン区画と、
ガスタービンエンジン(130)の要素の制御面を位置決めするアクチュエータ(124)と、
モデル出力の関数として前記アクチュエータ(124)に指示する制御法則(111)と、
前記モデル出力を生成するモデル処理装置(110)と、
を備えたガスタービンエンジン(130)において、
前記モデル処理装置(110)は、
モデル入力ベクトルを処理し、モデル動作モードを設定する入力オブジェクト(220)と、
前記モデル動作モードに基づいて、オープンループモデル(410)に入力される前記モデル処理装置(110)の動的状態を設定する設定状態モジュール(420)であって、前記オープンループモデル(410)が、前記動的状態および前記モデル入力ベクトルの関数として現在の状態の導関数、ソルバエラーベクトル、および合成パラメータを生成し、前記現在の状態の導関数およびソルバエラーベクトルへの制約が、一連のサイクル合成モジュールに基づき、前記一連のサイクル合成モジュールの各部が、前記ガスタービンエンジン(130)のサイクルの構成要素をモデル化し、一連のプログラムを備え、前記一連のプログラムが、前記構成要素の挙動に関わる物理法則の数学的抽象化に基づいている、設定状態モジュール(420)と、
前の状態、前記現在の状態の導関数、前記ソルバエラーベクトル、および前記合成パラメータのうちの少なくとも1つに基づいて前記モデルの推定状態を決定する推定状態モジュール(440)であって、前記モデルの推定状態を決定するために、オンライン線形化およびゲイン算出(441)を用いて推定器ゲインを決定する、推定状態モジュール(440)と、
前記モデル出力を決定するために前記モデルの少なくとも前記合成パラメータを処理する出力オブジェクト(240)と、
を備える、ガスタービンエンジン(130)。 - 前記オンライン線形化およびゲイン算出(441)は、現在の状態、前記モデル入力ベクトル、前記モデル出力、および前記合成パラメータに基づく偏導関数を取得すること(443)を含むことを特徴とする請求項16に記載のガスタービンエンジン(130)。
- 前記オンライン線形化およびゲイン算出(441)は、前記偏導関数を用いてゲイン設計のための線形システムを構築すること(445)をさらに含むことを特徴とする請求項17に記載のガスタービンエンジン(130)。
- 前記オンライン線形化およびゲイン算出(441)は、ゲイン設計のための前記線形システムに基づいて前記推定器ゲインを決定すること(447)をさらに含むことを特徴とする請求項18に記載のガスタービンエンジン(130)。
- 前記推定器ゲインは、エラーベクトルの最小化に用いられることを特徴とする請求項16に記載のガスタービンエンジン(130)。
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