401 lines
12 KiB
TeX
401 lines
12 KiB
TeX
\section{Modelisation}
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\begin{align*}
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\dot{x_{1}}, \dot{x_{2}} = f(e_{1},e_{2},q) & &
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\left\{ \begin{aligned}
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x_{1}(\zeta,t) &= \frac{\partial^{2}\omega}{\partial\varepsilon^{2}}\\
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x_{2}(\zeta,t) &= \rho(\zeta)\frac{\partial\omega}{dt}
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\end{aligned} \right. & &
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\left\{ \begin{aligned}
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e_{1}(\zeta,t) &= EI(\zeta)x_{1}\\
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e_{2}(\zeta,t) &= \frac{1}{\rho(\zeta)}x_{2} = \frac{\partial\omega}{\partial t}
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\end{aligned} \right.
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\end{align*}
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\subsection{Question 1}
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\begin{align}
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\left\{\begin{aligned}
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\dot{x_{1}} &= \frac{\partial x_{1}}{\partial t} = \frac{\partial}{\partial t} (\frac{\partial^2\omega}{\partial \zeta^2}) = \frac{\partial^2}{\partial \zeta^2}(\frac{\partial^2\omega}{\partial t})\\
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\dot{x_{2}} &= \rho(\zeta)\frac{\partial^2\omega}{\partial t} = \underbrace{-\frac{\partial^{2}}{\partial \zeta^2}(EI(\zeta)\frac{\partial^2\omega}{\partial\zeta^2})-q(\zeta,t)}_\text{EDP}
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\end{aligned}\right. & &
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\Rightarrow & &
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\boxed{\left\{\begin{aligned}
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\dot{x_{1}} &= \frac{\partial^2 e_2}{\partial\zeta^2} \\
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\dot{x_{2}} &= -\frac{\partial^2 e_1}{\partial\zeta^2}-q(\zeta,t)
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\end{aligned}\right. }
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\end{align}
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\subsection{Question 2}
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\begin{align*}
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\left\{\begin{aligned}
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x_1 &\approx \phi^Tx_{1d}(t) \\
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x_2 &\approx \phi^Tx_{2d}(t)
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\end{aligned}\right. & &
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\left\{\begin{aligned}
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e_1 &\approx \phi^Te_{1d}(t) \\
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e_2 &\approx \phi^Te_{2d}(t)
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\end{aligned}\right.
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\end{align*}
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En utilisant la première ligne de l'équation 1, on trouve :
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\begin{equation*}
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\int\phi(\zeta)d\zeta\times\phi^T\dot{x_{1d}} = \int\phi(\zeta)d\zeta\times\frac{\partial^2}{\partial\zeta^2} = \ddot{\phi}(\zeta)^Te_{2d}
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\end{equation*}
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\begin{equation}
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\underbrace{\int_{0}^{L}\phi(\zeta)\phi(\zeta)^Td\zeta}_\text{E}\times\dot{x_{1d}} = \left(\int_{0}^{L}\phi(\zeta)\ddot{\phi}(\zeta)d\zeta\right)e_{2d}
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\end{equation}
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On applique plusieurs fois de l’intégration par partie (IPP) :
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\begin{equation*}
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\begin{aligned}
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\int_{0}^{L}\phi(\zeta)\ddot{\phi}(\zeta)^T d\zeta &= [\phi(\zeta)\dot{\phi}(\zeta)^T]_{0}^{L} - \int_{0}^{L}\dot{\phi}(\zeta)\dot{\phi}(\zeta)^T d\zeta \\
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&= \phi(L)\dot{\phi}(L)^T - \underbrace{\phi(0)\dot{\phi}(0)^T }_\text{=0} - \dot{\phi}(L)\phi(L)^T + \underbrace{\dot{\phi(0)}\phi(0)^T }_\text{=0} + \int_{0}^{L} \ddot{\phi}(\zeta)\phi(\zeta)^T d\zeta \\
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&= \phi(L)\dot{\phi}(L)^T - \dot{\phi}(L)\phi(L)^T + \int_{0}^{L} \ddot{\phi}(\zeta)\phi(\zeta)^T d\zeta = D
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\end{aligned}
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\end{equation*}
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On continue avec ça en remplaçant dans l'équation 2 : $\Rightarrow \boxed{E\dot{x}_{1d} = De_{2d}}$ \\
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Puis on a dans la deuxième ligne de l'équation 1 :
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\begin{equation*}
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\begin{aligned}
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\phi^T(\zeta)\dot{x}_{2d} &= - \frac{\partial^2}{\partial\zeta^2} (\phi(\zeta)^T e_{1d}) - q(\zeta, t) \\
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\int_{0}^{L} \phi^T(\zeta)d\zeta\times\dot{x}_{2d} &= -e_{1d}\int_{0}^{L}\phi(\zeta)\ddot{\phi}(\zeta)^T d\zeta - \underbrace{\int_{0}^{L}\phi(\zeta)q(\zeta,t)d\zeta}_{=F_{ext}}
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\end{aligned}
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\end{equation*}
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Puis on trouve D :
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\begin{equation*}
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\begin{aligned}
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& D = \phi(L)\dot{\phi}(L)^T - \phi(L)\dot{\phi}(L)^T + \int_{0}^{L}\ddot{\phi}(\zeta)\phi(\zeta)^Td\zeta \\
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\Rightarrow & D^T = \dot{\phi}(L)\phi(L)^T - \dot{\phi}(L)\phi(L)^T + \int_{0}^{L}\phi(\zeta)\ddot{\phi}(\zeta)d\zeta \\
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\Rightarrow & \boxed{\int_{0}^{L}\underbrace{\phi(\zeta)}\ddot{\phi}(\zeta)^Td\zeta} = D^T - \dot{\phi}(L)\phi(L)^T + \phi(L)\dot{\phi}(L)^T \\
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\Rightarrow & E\dot{x}_{2d} = -e_{1d}D^T + \overbrace{e_{1d}\dot{\phi}(L)\phi(L)^T}^{=0} - e_{1d}\phi(L)\dot{\phi}(L)^T - F_{ext}
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\end{aligned}
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\end{equation*}
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Or on sait que :
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\begin{align*}
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\Rightarrow\left\{\begin{aligned}
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\frac{de_1}{d\zeta} = u(t) &\Rightarrow \dot{\phi}(L)^T e_{1d} = u(t) \\
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e_1 (L,t) = 0 &\Rightarrow \phi(L)^T e_{1d} = 0
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\end{aligned}\right. & &
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\Rightarrow & &
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\boxed{E\dot{x}_{2d} = - e_{1d}D^T - \phi(L)u(t) - F_{ext}}
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\end{align*}
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Puis on a ceci :
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\begin{align*}
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\left\{\begin{aligned}
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y(t) &= -e_2 (L,t) \\
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e_2 (L,t) &\approx \phi(L)^T e_{2d}
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\end{aligned}\right. & &
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\Rightarrow & &
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\boxed{y(t) = -\phi(L)^T e_{2d}}
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\end{align*}
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\subsection{Question 3}
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On a :
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\begin{equation*}
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\left\{\begin{aligned}
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e_1 = EIx_1 = x_1 &\Rightarrow e_{1d} = x_{1d} \\
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e_2 = \frac{1}{\rho(\zeta)}x_2 = x_2 &\Rightarrow e_{2d} = x_{2d}
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\end{aligned}\right.
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\end{equation*}
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Donc :
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\begin{equation*}
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\left\{\begin{aligned}
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E\dot{X}_{1d} &= Dx_{2d} \\
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E\dot{X}_{2d} &= -D^T x_{1d} - \phi(L)u(t) - 0 \\
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y &= -\phi(L)^T x_{2d}
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\end{aligned}\right.
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\end{equation*}
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Ce qui nous donne :
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\begin{equation*}
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A = \begin{pmatrix}
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0 & E^{-1}D \\
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-E^{-1}D^T & 0
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\end{pmatrix}, \ B = \begin{pmatrix}
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0 \\
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-E^{-1}\phi(L)
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\end{pmatrix}, \ C = \begin{pmatrix}
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0 & -\phi(L)^T
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\end{pmatrix}
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\end{equation*}
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Pour :
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\begin{equation*}
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\left\{\begin{aligned}
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\zeta = L = 1 \\
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\phi(1) = \begin{pmatrix}
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0 \\
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1 \\
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0 \\
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0
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\end{pmatrix}
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\end{aligned}\right.
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\end{equation*}
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\begin{equation*}
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A = \begin{pmatrix}
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0 & 0 & 0 & 0 & 114 & 6 & 12 & -2 \\
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0 & 0 & 0 & 0 & -54 & 6 & -2 & 4 \\
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0 & 0 & 0 & 0 & -1188 & -12 & -114 & 6 \\
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0 & 0 & 0 & 0 & -828 & -12 & -54 & 0 \\
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6 & 54 & 4 & -2 & 0 & 0 & 0 & 0 \\
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-6 & -114 & -2 & 12 & 0 & 0 & 0 & 0 \\
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-12 & -828 & -6 & 54 & 0 & 0 & 0 & 0 \\
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-12 & -1188 & -6 & 114 & 0 & 0 & 0 & 0 \\
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\end{pmatrix}, \ B = \begin{pmatrix}
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0 \\
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0 \\
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0 \\
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0 \\
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4 \\
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-16 \\
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-60 \\
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-120 \\
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\end{pmatrix}, \ C = \begin{pmatrix}
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0 & 0 & 0 & 0 & 0 & -1 & 0 & 0
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\end{pmatrix}
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\end{equation*}
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\subsection{Question 4}
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\begin{equation*}
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\omega(p, t) = C_\omega(p)x_d(t)
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\end{equation*}
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\begin{equation*}
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C_\omega(p) = \begin{bmatrix}
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\frac{p^2(2p^3-5p^2+10)}{20} & -\frac{p^4(2p-5)}{20} & \frac{p^3(3p^2-10p+10)}{60} & \frac{p^4(3p-5)}{60} & 0 & 0 & 0 & 0
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\end{bmatrix}
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\end{equation*}
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\begin{equation*}
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\phi(L)^T = \begin{bmatrix}
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2p^3 - 3p^2 + 1 & 3p^2 - 2p^3 & p^3 - 2p^2 + p & p^3 - p^2
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\end{bmatrix}
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\end{equation*}
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\includegraphics[width=\textwidth]{Illustrations/Question4}
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\subsection{Question 5}
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\includegraphics[width=\textwidth]{Illustrations/Question5}\begin{align*}
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y = -\phi(L)^Te_{2d} && y = -e_2(L, t) & & e_2(\zeta, t) \approx \phi(\zeta)^Te_{2d}(t)
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\end{align*}
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\begin{align*}
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x_1 = \frac{\partial^2\omega}{\partial\zeta^2}(\zeta,t)\approx\phi(\zeta)^2x_{1d} & & x_2(\zeta,t) = \rho(\zeta)\frac{\partial\omega}{\partial t}(\zeta,t) \approx\phi(\zeta)^Tx_{2d}
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\end{align*}
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\begin{align*}
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\begin{bmatrix}
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\dot{x}_{1d} \\ \dot{x}_{1d}
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\end{bmatrix} = A \begin{bmatrix}
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x_{1d} \\ x_{2d}
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\end{bmatrix} + Bu & & y = C \begin{bmatrix}
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x_{1d} \\ x_{2d}
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\end{bmatrix}
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\end{align*}
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\subsection{Question 6}
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\begin{equation*}
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\begin{bmatrix}
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x_1 \\ x_2
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\end{bmatrix} = \begin{bmatrix}
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\frac{\partial^2\omega}{\partial\zeta^2}(\zeta,t) \\
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\rho(\zeta)\frac{\partial\omega}{\partial t}(\zeta,t)
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\end{bmatrix} = \begin{bmatrix}
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\phi(\zeta)^T & 0000 \\
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0000 & \phi(\zeta)^T
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\end{bmatrix} \begin{bmatrix}
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x_{1d} \\ x_{2d}
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\end{bmatrix}
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\end{equation*}
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\begin{equation*}
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\frac{\partial^2\omega}{\partial\zeta^2}(\zeta,t) = \underbrace{\begin{bmatrix}
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\phi(\zeta)^T & 0 & 0 & 0 & 0
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\end{bmatrix}}_{C.I.=0+0}x_{d}(t)
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\end{equation*}
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\begin{equation*}
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\begin{aligned}
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\frac{\partial\omega}{\partial\zeta}(\zeta,t) &= \int\frac{\partial^2\omega}{\partial\zeta^2}(\zeta,t)d\zeta = x_d(t)\int\begin{bmatrix}
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\phi(\zeta)^T & 0 & 0 & 0 & 0
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\end{bmatrix}d\zeta + C_1(t) \\
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\omega(\zeta,t) &= \int\int\frac{\partial^2\omega}{\partial^2\zeta^2}(\zeta,t)d\zeta^2 = x_d(t)\int\int\begin{bmatrix}
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\phi(\zeta)^T & 0 & 0 & 0 & 0
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\end{bmatrix}d\zeta^2 + \underbrace{\int C_1(t)d\zeta + C_2(t)}_{\zeta C_1(t) + C_2(t)}
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\end{aligned}
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\end{equation*}
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$C_1$ et $C_2$ ?????????????????
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\section{Retour de sortie}
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\subsection{Question 7}
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La sortie est donnée par $y(t) = C\,x_d(t)$, donc le système en boucle fermée s’écrit :
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\begin{equation*}
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\begin{cases}
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\dot{x}_d(t) = (A - B C k)\,x_d(t) + B H\,w_c(L,t) \\
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w(L,t) = C_w(L)\,x_d(t)
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\end{cases}
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\end{equation*}
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En régime permanent, $\dot{x}_d(t)=0$, donc :
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\begin{equation*}
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0 = (A - B C k)\,x_d + B H\,C_w(L)\,x_d
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\quad \Rightarrow \quad
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x_d = -(A - B C k)^{-1} B H w_c(L,t)
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\end{equation*}
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En multipliant l’expression par $C_w(L)$, on trouve :
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\begin{equation*}
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w(L,t) = C_w(L)\,x_d = -C_w(L)(A - B C k)^{-1} B H w_c(L,t)
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\end{equation*}
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Pour assurer le suivi $w(L,t) = w_c(L,t)$, il faut :
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\begin{equation*}
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- C_w(L)(A - B C k)^{-1} B H = I
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\end{equation*}
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D’où :
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\begin{equation*}
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\boxed{H = -\left(C_w(L)(A - B C k)^{-1} B\right)^{-1}}
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\end{equation*}
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Finalement, après calcul sous MATLAB, on obtient $H = -3$.
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\subsection{Question 8}
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\includegraphics[width=\textwidth]{Illustrations/Question8}
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\subsection{Question 9}
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\subsection{Question 10}
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\section{Retour d'état}
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\subsection{Question 11}
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En utilisant la fonction \texttt{lqr()} de MATLAB avec $Q = I_8$ et $R = 1$, on trouve la matrice de gain $K$ suivante :
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\begin{equation*}
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K = \begin{pmatrix}
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0.97 & -14.62 & 0.66 & 1.32 & 19.32 & 0.39 & 2.40 & -2.11
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\end{pmatrix}
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\end{equation*}
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\subsection{Question 12}
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\includegraphics[width=\textwidth]{Illustrations/Question12}
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\subsection{Question 13}
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\includegraphics[width=\textwidth]{Illustrations/Question13}
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\subsection{Question 14}
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\includegraphics[width=\textwidth]{Illustrations/Question14}
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\section{Rejection de perturbation}
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\subsection{Question 15}
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On sait que :
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\begin{equation*}
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F_{ext} = \int_{0}^{L}\phi(\zeta)q(\zeta,t)d\zeta
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\quad \Rightarrow \quad
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F_{ext} = q_0(t) \cdot \int_{0}^{L}\phi(\zeta)d\zeta \text{ car } q(\zeta,t) = q_0(t)
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\end{equation*}
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Or on a :
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\begin{equation*}
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E\dot{x}_{2d} = - e_{1d}D^T - \phi(L)u(t) - F_{ext}
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\end{equation*}
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Donc, puisque $\dot{x}_{d}(t) = A x_d(t) + B u(t) + B_p q_0(t)$, on trouve :
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\begin{equation*}
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B_p =
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\begin{pmatrix}
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0_{4 \times 1} \\
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-\int_{0}^{L}\phi(\zeta)d\zeta
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\end{pmatrix}
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=
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\begin{pmatrix}
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0_{4 \times 1} \\
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\frac{1}{2} \\
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\frac{1}{2} \\
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\frac{1}{12} \\
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-\frac{1}{12}
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\end{pmatrix}
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\end{equation*}
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\subsection{Question 16}
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\includegraphics[width=\textwidth]{Illustrations/Question16}
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Notre système ne permet pas de garantir une erreur nulle en régime permanent face
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à une perturbation constante.
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\subsection{Question 17}
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Nous souhaitons garder les mêmes valeurs propres que celles obtenues lors de la question 11
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avec la LQR. La valeur propre supplémentaire doit être plus à droite pour permettre
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de rejeter la perturbation. On chosit $\lambda_9 = -2$.
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On trouve alors :
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\begin{equation*}
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\lambda = \begin{pmatrix}
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-84.66 & -7.56 \pm 68.77i & -27.97 \pm 17.24i & -15.91 & -4.38 \pm 2.66i & -2
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\end{pmatrix}^T
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\end{equation*}
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\subsection{Question 18}
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En utilisant la fonction \texttt{place()} de MATLAB, on trouve la matrice de gain $K$ suivante :
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\begin{equation*}
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K_{aug} =
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\begin{pmatrix}
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K_1 & K_i
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\end{pmatrix}
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\quad \text{avec} \quad
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K_1 \in \mathbb{R}^{1 \times 8}, \;
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K_i \in \mathbb{R}
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\end{equation*}
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\begin{equation*}
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K_{aug} = \begin{pmatrix}
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-0.89 & -16.59 & 0.28 & 1.68 & 19.39 & -0.84 & 2.36 & -1.94 & 12.00
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\end{pmatrix}
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\end{equation*}
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\subsection{Question 19}
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\includegraphics[width=\textwidth]{Illustrations/Question19}
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En utilisant l'action intégrale, on parvient à rejeter la perturbation constante
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et à garantir une erreur nulle en régime permanent.
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\subsection{Question 20}
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Nous pouvons utiliser les mêmes gains $K_1$ et $K_i$ dans l'implémentation avec un contrôleur
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numérique en prenant une période d'échantillonnage suffisamment court. La période d'échantillonnage
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maximale garantissant la stabilité asymptotique est de $T_s = 0.01066 [s]$.
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En divisant la période d'échantillonnage par 5 soit $T_s \approx 0.002 [s]$, on obtient une réponse du système
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répondant à la performance désirée et à la stabilité.
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