519 lines
23 KiB
HTML
519 lines
23 KiB
HTML
<?xml version="1.0" encoding="utf-8"?>
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN"
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<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en">
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<head>
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<!-- 2020-11-12 jeu. 09:18 -->
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<meta http-equiv="Content-Type" content="text/html;charset=utf-8" />
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<title>Test Bench APA95ML</title>
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<meta name="generator" content="Org mode" />
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<meta name="author" content="Dehaeze Thomas" />
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<link rel="stylesheet" type="text/css" href="./css/htmlize.css"/>
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<link rel="stylesheet" type="text/css" href="./css/readtheorg.css"/>
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<script type="text/javascript" src="./js/readtheorg.js"></script>
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</head>
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<body>
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<div id="org-div-home-and-up">
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<a accesskey="h" href="../index.html"> UP </a>
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<a accesskey="H" href="../index.html"> HOME </a>
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</div><div id="content">
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<h1 class="title">Test Bench APA95ML</h1>
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<div id="table-of-contents">
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<h2>Table of Contents</h2>
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<div id="text-table-of-contents">
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<ul>
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<li><a href="#orge1ce8ff">1. Setup</a>
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<ul>
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<li><a href="#org4f8d088">1.1. Parameters</a></li>
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<li><a href="#org92bcdf4">1.2. Filter White Noise</a></li>
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</ul>
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</li>
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<li><a href="#org17a026f">2. Run Experiment and Save Data</a>
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<ul>
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<li><a href="#org1b14494">2.1. Load Data</a></li>
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<li><a href="#org59026b4">2.2. Save Data</a></li>
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</ul>
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</li>
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<li><a href="#org1758121">3. Huddle Test</a>
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<ul>
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<li><a href="#org7fcc745">3.1. Time Domain Data</a></li>
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<li><a href="#org67ec115">3.2. PSD of Measurement Noise</a></li>
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</ul>
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</li>
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<li><a href="#org3be6abe">4. Transfer Function Estimation using the PI Amplifier</a>
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<ul>
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<li><a href="#orgd263f64">4.1. Load Data</a></li>
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<li><a href="#orga450ffc">4.2. Comparison of the PSD with Huddle Test</a></li>
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<li><a href="#orgc964fb2">4.3. Compute TF estimate and Coherence</a></li>
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<li><a href="#orge2ba96a">4.4. Comparison with the FEM model</a></li>
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</ul>
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</li>
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<li><a href="#org1988c0d">5. Transfer function from force actuator to force sensor</a>
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<ul>
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<li><a href="#org037188e">5.1. System Identification</a></li>
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<li><a href="#org0a38226">5.2. Integral Force Feedback</a></li>
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</ul>
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</li>
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<li><a href="#org5df0163">6. IFF Tests</a>
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<ul>
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<li><a href="#org26f64e8">6.1. First tests with few gains</a></li>
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<li><a href="#orgda4dc48">6.2. Second test with many Gains</a></li>
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</ul>
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</li>
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</ul>
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</div>
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</div>
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<div id="orgf655a68" class="figure">
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<p><img src="figs/setup_picture.png" alt="setup_picture.png" />
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</p>
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<p><span class="figure-number">Figure 1: </span>Picture of the Setup</p>
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</div>
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<div id="org9083f49" class="figure">
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<p><img src="figs/setup_zoom.png" alt="setup_zoom.png" />
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</p>
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<p><span class="figure-number">Figure 2: </span>Zoom on the APA</p>
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</div>
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<div id="outline-container-orge1ce8ff" class="outline-2">
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<h2 id="orge1ce8ff"><span class="section-number-2">1</span> Setup</h2>
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<div class="outline-text-2" id="text-1">
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</div>
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<div id="outline-container-org4f8d088" class="outline-3">
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<h3 id="org4f8d088"><span class="section-number-3">1.1</span> Parameters</h3>
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<div class="outline-text-3" id="text-1-1">
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<div class="org-src-container">
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<pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4;
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</pre>
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</div>
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</div>
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</div>
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<div id="outline-container-org92bcdf4" class="outline-3">
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<h3 id="org92bcdf4"><span class="section-number-3">1.2</span> Filter White Noise</h3>
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<div class="outline-text-3" id="text-1-2">
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<div class="org-src-container">
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<pre class="src src-matlab">Glpf = 1<span class="org-type">/</span>(1 <span class="org-type">+</span> s<span class="org-type">/</span>2<span class="org-type">/</span><span class="org-constant">pi</span><span class="org-type">/</span>500);
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Gz = c2d(Glpf, Ts, <span class="org-string">'tustin'</span>);
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</pre>
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</div>
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</div>
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</div>
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</div>
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<div id="outline-container-org17a026f" class="outline-2">
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<h2 id="org17a026f"><span class="section-number-2">2</span> Run Experiment and Save Data</h2>
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<div class="outline-text-2" id="text-2">
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</div>
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<div id="outline-container-org1b14494" class="outline-3">
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<h3 id="org1b14494"><span class="section-number-3">2.1</span> Load Data</h3>
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<div class="outline-text-3" id="text-2-1">
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<div class="org-src-container">
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<pre class="src src-matlab">data = SimulinkRealTime.utils.getFileScopeData(<span class="org-string">'data/apa95ml.dat'</span>).data;
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</pre>
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</div>
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</div>
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</div>
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<div id="outline-container-org59026b4" class="outline-3">
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<h3 id="org59026b4"><span class="section-number-3">2.2</span> Save Data</h3>
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<div class="outline-text-3" id="text-2-2">
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<div class="org-src-container">
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<pre class="src src-matlab">u = data(<span class="org-type">:</span>, 1); <span class="org-comment">% Input Voltage [V]</span>
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y = data(<span class="org-type">:</span>, 2); <span class="org-comment">% Output Displacement [m]</span>
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t = data(<span class="org-type">:</span>, 3); <span class="org-comment">% Time [s]</span>
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</pre>
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</div>
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<div class="org-src-container">
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<pre class="src src-matlab">save(<span class="org-string">'./mat/huddle_test.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'u'</span>, <span class="org-string">'y'</span>, <span class="org-string">'Glpf'</span>);
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</pre>
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</div>
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</div>
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</div>
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</div>
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<div id="outline-container-org1758121" class="outline-2">
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<h2 id="org1758121"><span class="section-number-2">3</span> Huddle Test</h2>
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<div class="outline-text-2" id="text-3">
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</div>
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<div id="outline-container-org7fcc745" class="outline-3">
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<h3 id="org7fcc745"><span class="section-number-3">3.1</span> Time Domain Data</h3>
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<div class="outline-text-3" id="text-3-1">
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<div id="orge79b739" class="figure">
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<p><img src="figs/huddle_test_time_domain.png" alt="huddle_test_time_domain.png" />
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</p>
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<p><span class="figure-number">Figure 3: </span>Measurement of the Mass displacement during Huddle Test</p>
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</div>
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</div>
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</div>
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<div id="outline-container-org67ec115" class="outline-3">
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<h3 id="org67ec115"><span class="section-number-3">3.2</span> PSD of Measurement Noise</h3>
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<div class="outline-text-3" id="text-3-2">
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<div class="org-src-container">
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<pre class="src src-matlab">Ts = t(end)<span class="org-type">/</span>(length(t)<span class="org-type">-</span>1);
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Fs = 1<span class="org-type">/</span>Ts;
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win = hanning(ceil(1<span class="org-type">*</span>Fs));
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</pre>
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</div>
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<div class="org-src-container">
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<pre class="src src-matlab">[pxx, f] = pwelch(y(1000<span class="org-type">:</span>end), win, [], [], Fs);
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</pre>
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</div>
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<div id="org8f41c21" class="figure">
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<p><img src="figs/huddle_test_pdf.png" alt="huddle_test_pdf.png" />
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</p>
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<p><span class="figure-number">Figure 4: </span>Amplitude Spectral Density of the Displacement during Huddle Test</p>
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</div>
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</div>
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</div>
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</div>
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<div id="outline-container-org3be6abe" class="outline-2">
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<h2 id="org3be6abe"><span class="section-number-2">4</span> Transfer Function Estimation using the PI Amplifier</h2>
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<div class="outline-text-2" id="text-4">
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</div>
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<div id="outline-container-orgd263f64" class="outline-3">
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<h3 id="orgd263f64"><span class="section-number-3">4.1</span> Load Data</h3>
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<div class="outline-text-3" id="text-4-1">
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<div class="org-src-container">
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<pre class="src src-matlab">ht = load(<span class="org-string">'./mat/huddle_test.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'u'</span>, <span class="org-string">'y'</span>);
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load(<span class="org-string">'./mat/apa95ml_5kg_Amp_E505.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'u'</span>, <span class="org-string">'um'</span>, <span class="org-string">'y'</span>);
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</pre>
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</div>
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<div class="org-src-container">
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<pre class="src src-matlab">u = 10<span class="org-type">*</span>(u <span class="org-type">-</span> mean(u)); <span class="org-comment">% Input Voltage of Piezo [V]</span>
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um = 10<span class="org-type">*</span>(um <span class="org-type">-</span> mean(um)); <span class="org-comment">% Monitor [V]</span>
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y = y <span class="org-type">-</span> mean(y); <span class="org-comment">% Mass displacement [m]</span>
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ht.u = 10<span class="org-type">*</span>(ht.u <span class="org-type">-</span> mean(ht.u));
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ht.y = ht.y <span class="org-type">-</span> mean(ht.y);
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</pre>
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</div>
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</div>
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</div>
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<div id="outline-container-orga450ffc" class="outline-3">
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<h3 id="orga450ffc"><span class="section-number-3">4.2</span> Comparison of the PSD with Huddle Test</h3>
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<div class="outline-text-3" id="text-4-2">
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<div class="org-src-container">
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<pre class="src src-matlab">Ts = t(end)<span class="org-type">/</span>(length(t)<span class="org-type">-</span>1);
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Fs = 1<span class="org-type">/</span>Ts;
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win = hanning(ceil(1<span class="org-type">*</span>Fs));
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</pre>
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</div>
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<div class="org-src-container">
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<pre class="src src-matlab">[pxx, f] = pwelch(y, win, [], [], Fs);
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[pht, <span class="org-type">~</span>] = pwelch(ht.y, win, [], [], Fs);
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</pre>
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</div>
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<div id="orge6cd415" class="figure">
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<p><img src="figs/apa95ml_5kg_PI_pdf_comp_huddle.png" alt="apa95ml_5kg_PI_pdf_comp_huddle.png" />
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</p>
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<p><span class="figure-number">Figure 5: </span>Comparison of the ASD for the identification test and the huddle test</p>
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</div>
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</div>
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</div>
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<div id="outline-container-orgc964fb2" class="outline-3">
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<h3 id="orgc964fb2"><span class="section-number-3">4.3</span> Compute TF estimate and Coherence</h3>
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<div class="outline-text-3" id="text-4-3">
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<div class="org-src-container">
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<pre class="src src-matlab">Ts = t(end)<span class="org-type">/</span>(length(t)<span class="org-type">-</span>1);
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Fs = 1<span class="org-type">/</span>Ts;
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</pre>
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</div>
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<div class="org-src-container">
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<pre class="src src-matlab">win = hann(ceil(1<span class="org-type">/</span>Ts));
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[tf_est, f] = tfestimate(u, <span class="org-type">-</span>y, win, [], [], 1<span class="org-type">/</span>Ts);
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[tf_um , <span class="org-type">~</span>] = tfestimate(um, <span class="org-type">-</span>y, win, [], [], 1<span class="org-type">/</span>Ts);
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[co_est, <span class="org-type">~</span>] = mscohere( um, <span class="org-type">-</span>y, win, [], [], 1<span class="org-type">/</span>Ts);
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</pre>
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</div>
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<div id="orgc5081fd" class="figure">
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<p><img src="figs/apa95ml_5kg_PI_coh.png" alt="apa95ml_5kg_PI_coh.png" />
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</p>
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<p><span class="figure-number">Figure 6: </span>Coherence</p>
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</div>
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<div id="orgef956d1" class="figure">
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<p><img src="figs/apa95ml_5kg_PI_tf.png" alt="apa95ml_5kg_PI_tf.png" />
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</p>
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<p><span class="figure-number">Figure 7: </span>Estimation of the transfer function from input voltage to displacement</p>
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</div>
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</div>
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</div>
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<div id="outline-container-orge2ba96a" class="outline-3">
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<h3 id="orge2ba96a"><span class="section-number-3">4.4</span> Comparison with the FEM model</h3>
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<div class="outline-text-3" id="text-4-4">
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<div class="org-src-container">
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<pre class="src src-matlab">load(<span class="org-string">'mat/fem_model_5kg.mat'</span>, <span class="org-string">'G'</span>);
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</pre>
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</div>
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<div id="org5df5018" class="figure">
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<p><img src="figs/apa95ml_5kg_pi_comp_fem.png" alt="apa95ml_5kg_pi_comp_fem.png" />
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</p>
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<p><span class="figure-number">Figure 8: </span>Comparison of the identified transfer function and the one estimated from the FE model</p>
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</div>
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</div>
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</div>
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</div>
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<div id="outline-container-org1988c0d" class="outline-2">
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<h2 id="org1988c0d"><span class="section-number-2">5</span> Transfer function from force actuator to force sensor</h2>
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<div class="outline-text-2" id="text-5">
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<p>
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Two measurements are performed:
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</p>
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<ul class="org-ul">
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<li>Speedgoat DAC => Voltage Amplifier (x20) => 1 Piezo Stack => … => 2 Stacks as Force Sensor (parallel) => Speedgoat ADC</li>
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<li>Speedgoat DAC => Voltage Amplifier (x20) => 2 Piezo Stacks (parallel) => … => 1 Stack as Force Sensor => Speedgoat ADC</li>
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</ul>
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<p>
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The obtained dynamics from force actuator to force sensor are compare with the FEM model.
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</p>
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<p>
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The data are loaded:
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</p>
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<div class="org-src-container">
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<pre class="src src-matlab">a_ss = load(<span class="org-string">'mat/apa95ml_5kg_1a_2s.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'u'</span>, <span class="org-string">'y'</span>, <span class="org-string">'v'</span>);
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aa_s = load(<span class="org-string">'mat/apa95ml_5kg_2a_1s.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'u'</span>, <span class="org-string">'y'</span>, <span class="org-string">'v'</span>);
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load(<span class="org-string">'mat/G_force_sensor_5kg.mat'</span>, <span class="org-string">'G'</span>);
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</pre>
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</div>
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<p>
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Let’s use the amplifier gain to obtain the true voltage applied to the actuator stack(s)
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</p>
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<p>
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The parameters of the piezoelectric stacks are defined below:
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</p>
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<div class="org-src-container">
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<pre class="src src-matlab">d33 = 3e<span class="org-type">-</span>10; <span class="org-comment">% Strain constant [m/V]</span>
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n = 80; <span class="org-comment">% Number of layers per stack</span>
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eT = 1.6e<span class="org-type">-</span>8; <span class="org-comment">% Permittivity under constant stress [F/m]</span>
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sD = 2e<span class="org-type">-</span>11; <span class="org-comment">% Elastic compliance under constant electric displacement [m2/N]</span>
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ka = 235e6; <span class="org-comment">% Stack stiffness [N/m]</span>
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</pre>
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</div>
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<p>
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From the FEM, we construct the transfer function from DAC voltage to ADC voltage.
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</p>
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<div class="org-src-container">
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<pre class="src src-matlab">Gfem_aa_s = exp(<span class="org-type">-</span>s<span class="org-type">/</span>1e4)<span class="org-type">*</span>20<span class="org-type">*</span>(2<span class="org-type">*</span>d33<span class="org-type">*</span>n<span class="org-type">*</span>ka)<span class="org-type">*</span>(G(3,1)<span class="org-type">+</span>G(3,2))<span class="org-type">*</span>d33<span class="org-type">/</span>(eT<span class="org-type">*</span>sD<span class="org-type">*</span>n);
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Gfem_a_ss = exp(<span class="org-type">-</span>s<span class="org-type">/</span>1e4)<span class="org-type">*</span>20<span class="org-type">*</span>( d33<span class="org-type">*</span>n<span class="org-type">*</span>ka)<span class="org-type">*</span>(G(3,1)<span class="org-type">+</span>G(2,1))<span class="org-type">*</span>d33<span class="org-type">/</span>(eT<span class="org-type">*</span>sD<span class="org-type">*</span>n);
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</pre>
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</div>
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<p>
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The transfer function from input voltage to output voltage are computed and shown in Figure <a href="#orge6ce288">9</a>.
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</p>
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<div class="org-src-container">
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<pre class="src src-matlab">Ts = a_ss.t(end)<span class="org-type">/</span>(length(a_ss.t)<span class="org-type">-</span>1);
|
|
Fs = 1<span class="org-type">/</span>Ts;
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|
|
|
win = hann(ceil(10<span class="org-type">/</span>Ts));
|
|
|
|
[tf_a_ss, f] = tfestimate(a_ss.u, a_ss.v, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
[coh_a_ss, <span class="org-type">~</span>] = mscohere( a_ss.u, a_ss.v, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
|
|
[tf_aa_s, f] = tfestimate(aa_s.u, aa_s.v, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
[coh_aa_s, <span class="org-type">~</span>] = mscohere( aa_s.u, aa_s.v, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
</pre>
|
|
</div>
|
|
|
|
|
|
<div id="orge6ce288" class="figure">
|
|
<p><img src="figs/bode_plot_force_sensor_voltage_comp_fem.png" alt="bode_plot_force_sensor_voltage_comp_fem.png" />
|
|
</p>
|
|
<p><span class="figure-number">Figure 9: </span>Comparison of the identified dynamics from voltage output to voltage input and the FEM</p>
|
|
</div>
|
|
</div>
|
|
|
|
<div id="outline-container-org037188e" class="outline-3">
|
|
<h3 id="org037188e"><span class="section-number-3">5.1</span> System Identification</h3>
|
|
<div class="outline-text-3" id="text-5-1">
|
|
<div class="org-src-container">
|
|
<pre class="src src-matlab">w_z = 2<span class="org-type">*</span><span class="org-constant">pi</span><span class="org-type">*</span>111; <span class="org-comment">% Zeros frequency [rad/s]</span>
|
|
w_p = 2<span class="org-type">*</span><span class="org-constant">pi</span><span class="org-type">*</span>255; <span class="org-comment">% Pole frequency [rad/s]</span>
|
|
xi_z = 0.05;
|
|
xi_p = 0.015;
|
|
G_inf = 2;
|
|
|
|
Gi = G_inf<span class="org-type">*</span>(s<span class="org-type">^</span>2 <span class="org-type">-</span> 2<span class="org-type">*</span>xi_z<span class="org-type">*</span>w_z<span class="org-type">*</span>s <span class="org-type">+</span> w_z<span class="org-type">^</span>2)<span class="org-type">/</span>(s<span class="org-type">^</span>2 <span class="org-type">+</span> 2<span class="org-type">*</span>xi_p<span class="org-type">*</span>w_p<span class="org-type">*</span>s <span class="org-type">+</span> w_p<span class="org-type">^</span>2);
|
|
</pre>
|
|
</div>
|
|
|
|
|
|
<div id="orged1dc40" class="figure">
|
|
<p><img src="figs/iff_plant_identification_apa95ml.png" alt="iff_plant_identification_apa95ml.png" />
|
|
</p>
|
|
<p><span class="figure-number">Figure 10: </span>Identification of the IFF plant</p>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
|
|
<div id="outline-container-org0a38226" class="outline-3">
|
|
<h3 id="org0a38226"><span class="section-number-3">5.2</span> Integral Force Feedback</h3>
|
|
<div class="outline-text-3" id="text-5-2">
|
|
|
|
<div id="org86c0c5b" class="figure">
|
|
<p><img src="figs/root_locus_iff_apa95ml_identification.png" alt="root_locus_iff_apa95ml_identification.png" />
|
|
</p>
|
|
<p><span class="figure-number">Figure 11: </span>Root Locus for IFF</p>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div id="outline-container-org5df0163" class="outline-2">
|
|
<h2 id="org5df0163"><span class="section-number-2">6</span> IFF Tests</h2>
|
|
<div class="outline-text-2" id="text-6">
|
|
</div>
|
|
<div id="outline-container-org26f64e8" class="outline-3">
|
|
<h3 id="org26f64e8"><span class="section-number-3">6.1</span> First tests with few gains</h3>
|
|
<div class="outline-text-3" id="text-6-1">
|
|
<div class="org-src-container">
|
|
<pre class="src src-matlab">iff_g10 = load(<span class="org-string">'./mat/apa95ml_iff_g10_res.mat'</span>, <span class="org-string">'u'</span>, <span class="org-string">'t'</span>, <span class="org-string">'y'</span>, <span class="org-string">'v'</span>);
|
|
iff_g100 = load(<span class="org-string">'./mat/apa95ml_iff_g100_res.mat'</span>, <span class="org-string">'u'</span>, <span class="org-string">'t'</span>, <span class="org-string">'y'</span>, <span class="org-string">'v'</span>);
|
|
iff_of = load(<span class="org-string">'./mat/apa95ml_iff_off_res.mat'</span>, <span class="org-string">'u'</span>, <span class="org-string">'t'</span>, <span class="org-string">'y'</span>, <span class="org-string">'v'</span>);
|
|
</pre>
|
|
</div>
|
|
|
|
<div class="org-src-container">
|
|
<pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4;
|
|
win = hann(ceil(10<span class="org-type">/</span>Ts));
|
|
|
|
[tf_iff_g10, f] = tfestimate(iff_g10.u, iff_g10.y, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
[co_iff_g10, <span class="org-type">~</span>] = mscohere(iff_g10.u, iff_g10.y, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
|
|
[tf_iff_g100, f] = tfestimate(iff_g100.u, iff_g100.y, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
[co_iff_g100, <span class="org-type">~</span>] = mscohere(iff_g100.u, iff_g100.y, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
|
|
[tf_iff_of, <span class="org-type">~</span>] = tfestimate(iff_of.u, iff_of.y, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
[co_iff_of, <span class="org-type">~</span>] = mscohere(iff_of.u, iff_of.y, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
</pre>
|
|
</div>
|
|
|
|
|
|
<div id="org01c9bde" class="figure">
|
|
<p><img src="figs/iff_first_test_coherence.png" alt="iff_first_test_coherence.png" />
|
|
</p>
|
|
<p><span class="figure-number">Figure 12: </span>Coherence</p>
|
|
</div>
|
|
|
|
|
|
|
|
<div id="orgdcd9122" class="figure">
|
|
<p><img src="figs/iff_first_test_bode_plot.png" alt="iff_first_test_bode_plot.png" />
|
|
</p>
|
|
<p><span class="figure-number">Figure 13: </span>Bode plot for different values of IFF gain</p>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div id="outline-container-orgda4dc48" class="outline-3">
|
|
<h3 id="orgda4dc48"><span class="section-number-3">6.2</span> Second test with many Gains</h3>
|
|
<div class="outline-text-3" id="text-6-2">
|
|
<div class="org-src-container">
|
|
<pre class="src src-matlab">load(<span class="org-string">'./mat/apa95ml_iff_test.mat'</span>, <span class="org-string">'results'</span>);
|
|
</pre>
|
|
</div>
|
|
|
|
<div class="org-src-container">
|
|
<pre class="src src-matlab">Ts = 1e<span class="org-type">-</span>4;
|
|
win = hann(ceil(10<span class="org-type">/</span>Ts));
|
|
</pre>
|
|
</div>
|
|
|
|
<div class="org-src-container">
|
|
<pre class="src src-matlab">tf_iff = {zeros(1, length(results))};
|
|
co_iff = {zeros(1, length(results))};
|
|
g_iff = [0, 1, 5, 10, 50, 100];
|
|
|
|
<span class="org-keyword">for</span> <span class="org-variable-name"><span class="org-constant">i</span></span>=<span class="org-constant">1:length(results)</span>
|
|
[tf_est, f] = tfestimate(results{<span class="org-constant">i</span>}.u, results{<span class="org-constant">i</span>}.y, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
[co_est, <span class="org-type">~</span>] = mscohere(results{<span class="org-constant">i</span>}.u, results{<span class="org-constant">i</span>}.y, win, [], [], 1<span class="org-type">/</span>Ts);
|
|
|
|
tf_iff(<span class="org-constant">i</span>) = {tf_est};
|
|
co_iff(<span class="org-constant">i</span>) = {co_est};
|
|
<span class="org-keyword">end</span>
|
|
</pre>
|
|
</div>
|
|
|
|
|
|
<div id="org52a1b9d" class="figure">
|
|
<p><img src="figs/iff_results_bode_plots.png" alt="iff_results_bode_plots.png" />
|
|
</p>
|
|
</div>
|
|
|
|
<div class="org-src-container">
|
|
<pre class="src src-matlab">G_id = {zeros(1,length(results))};
|
|
|
|
f_start = 70; <span class="org-comment">% [Hz]</span>
|
|
f_end = 500; <span class="org-comment">% [Hz]</span>
|
|
|
|
<span class="org-keyword">for</span> <span class="org-variable-name"><span class="org-constant">i</span></span> = <span class="org-constant">1:length(results)</span>
|
|
tf_id = tf_iff{<span class="org-constant">i</span>}(sum(f<span class="org-type"><</span>f_start)<span class="org-type">:</span>length(f)<span class="org-type">-</span>sum(f<span class="org-type">></span>f_end));
|
|
f_id = f(sum(f<span class="org-type"><</span>f_start)<span class="org-type">:</span>length(f)<span class="org-type">-</span>sum(f<span class="org-type">></span>f_end));
|
|
|
|
gfr = idfrd(tf_id, 2<span class="org-type">*</span><span class="org-constant">pi</span><span class="org-type">*</span>f_id, Ts);
|
|
G_id(<span class="org-constant">i</span>) = {procest(gfr,<span class="org-string">'P2UDZ'</span>)};
|
|
<span class="org-keyword">end</span>
|
|
</pre>
|
|
</div>
|
|
|
|
|
|
<div id="orga4ab0d0" class="figure">
|
|
<p><img src="figs/iff_results_bode_plots_identification.png" alt="iff_results_bode_plots_identification.png" />
|
|
</p>
|
|
</div>
|
|
|
|
|
|
<div id="org9a011df" class="figure">
|
|
<p><img src="figs/iff_results_root_locus.png" alt="iff_results_root_locus.png" />
|
|
</p>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
<div id="postamble" class="status">
|
|
<p class="author">Author: Dehaeze Thomas</p>
|
|
<p class="date">Created: 2020-11-12 jeu. 09:18</p>
|
|
</div>
|
|
</body>
|
|
</html>
|