twin mpc thesis

Author: RaffaeleGiuseppeCestari

thesis.md

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 <section id="master_thesis">
   <h2>2025</h2>
   <ul>
+
+    <li>
+      <strong>Twin-embedded MPC for longitudinal/lateral vehicle control</strong><br><br>
+      Development of a high-fidelity, physics-based vehicle dynamics simulator in Modelica/Dymola, integrated with a digital twin for predictive control tasks.<br><br>
+      <strong>Key question: Can we reliably initialize a simulator using observed vehicle states?</strong><br><br>
+      <strong>Tools & Skills:</strong> Modelica/Dymola, Python, Matlab, Simulink<br><br>
+      <ul>
+        <li><em>Development of physics-based and data-driven digital twins</em></li>
+        <li><em>Integration with Model Predictive Control frameworks</em></li>
+        <li><em>Testing in simulation with potential deployment on HIL platforms</em></li>
+      </ul>
+    </li>
+
     <li>
       <strong>Man-in-the-Middle (MiTM) Attack Detection [Cybersecurity/ML]</strong><br><br>
-      Development of MITM attacks detection algorithms for Resilient Predictive Control<br><br>
-      <strong>Kali Linux - Python - PyTorch/Tensorflow - Wireshark - Matlab - Simulink</strong><br><br>
+      Development of detection algorithms against MiTM attacks on control systems, focusing on resilient predictive controllers.<br><br>
+      <strong>Tools & Skills:</strong> Kali Linux, Python, PyTorch/TensorFlow, Wireshark, Matlab, Simulink<br><br>
       <ul>
-      <li>
-      <em>Experimental deployment on actual networks</em><br>
-      </li>
-      <li>
-      <em>Communication protocol in depth-study</em><br>
-      </li>
-       <li>
-      <em>Machine learning algorithms development</em><br>
-      </li>
-      <li>
-      <em>Resilient predictive controller development</em><br>
-      </li>
-  </ul>
+        <li><em>Experimental deployment on actual networks</em></li>
+        <li><em>In-depth study of industrial communication protocols</em></li>
+        <li><em>Development of ML-based intrusion detection algorithms</em></li>
+        <li><em>Design and testing of resilient predictive controllers under attack</em></li>
+      </ul>
     </li>
+
   </ul>
 </section>