Thesis update

40_CARNOT_model.tex

@@ -33,21 +33,8 @@ The Simulink model is then completed by adding a \textit{Weather Data File}
 containing weather measurements for a whole year, and a \textit{Weather
 Prediction} block responsible for sending weather predictions to the MPC.\@ The
 controller itself is defined in Python and is connected to Simulink via three
-TCP/IP sockets: one for sending the control signal, one for reading the
-temperature measurement, and one for reading the weather forecast.
-
-The final Simulink schema is presented in Figure~\ref{fig:CARNOT_complete}:
-
-\begin{figure}[ht]
-    \centering
-    \includegraphics[width = \textwidth]{Images/polydome_python.pdf}
-    \caption{Simulink Schema of the Complete Simulation}
-    \label{fig:CARNOT_complete}
-\end{figure}
-
-% TODO: [CARNOT] Redo this part
-
-\clearpage
+TCP/IP sockets. Details on the implementation are presented in
+Section~\ref{sec:implementation}.
 
 \subsection{Physical dimensions}\label{sec:Physical_dimensions}
 

50_Choice_of_Hyperparameters.tex

@@ -393,7 +393,7 @@ data, validating the model by analyzing its multi-step prediction performance
 ensures the model was able to learn the correct dynamics and is useful in
 simulation scenarios.
 
-The following subsections analyze the performance of the trained \arcshort{gp}
+The following subsections analyze the performance of the trained \acrshort{gp}
 and \acrshort{svgp} models over 20-step ahead predictions. For the \acrshort{gp}
 model the final choice of parameters is made according to the simulation
 performance. The simulation performance of the \acrshort{svgp} model is compared

70_Implementation.tex

@@ -1,4 +1,4 @@
-\section{Implementation}
+\section{Implementation}\label{sec:implementation}
 
 This section goes into the details of the implementation of the Simulink plant
 and Python controller setup.