chgt hyperref et placement paragraphes

This commit is contained in:
Nolan Reynier Nomer 2026-05-12 22:59:46 +02:00
parent ff8fee3dd9
commit 88a7ad1fb9
6 changed files with 368 additions and 161 deletions

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@ -66,7 +88,6 @@
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\OT1/ptm/m/it/10 2) Sim-u-la-tion and Con-trol: [][] \OT1/ptm/m/n/10 Based on
this model, a
[]
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[]\OT1/ptm/m/n/8 ------, ``lispbm in vesc,'' $https : / / github . com / vedder
b / bldc / tree / master /
[]\OT1/ptm/m/n/8 ------, ``lispbm in vesc,'' []$https : / / github . com / vedd
erb / bldc / tree / master /
[]
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@ -5,6 +5,7 @@
\usepackage{amsmath,amssymb,amsfonts}
\usepackage{algorithmic}
\usepackage{url}
\usepackage{hyperref}
\usepackage{placeins}
\usepackage{siunitx}
\usepackage{graphicx}
@ -79,13 +80,13 @@ attention to repairability, component sourcing, and community-centred sustainabi
design, assemble, and develop a functional, low-tech and open-source motor controller for electric cargo bikes. The
current model uses an open-source motor control called VESC (Vedder Electronic Speed Controller) that allows precise
control of electric motors. The controller needs to be compatible with a VESC controller and easily locally repairable
by the MAD. By exploring the inner workings of the VESC project, modelling of the physical systems and the Printed Circuit
Board (PCB) we investigated the ways we could do it in another way. We acquired a VESC controller to compare our system
and a commercial product. Preliminary results demonstrate that the adapted VESC-based controller successfully drives
the target motor under both commutation strategies, and that positional control is achievable with the current hardware
configuration. Security vulnerabilities related to open Bluetooth access were identified. These findings suggest that
open-source, locally fabricated motor controllers can meet the functional requirements of electric cargo bikes while
significantly improving repairability.
by the MAD. By exploring the inner workings of the VESC project, modelling of the physical systems and the Printed
Circuit Board (PCB) we investigated the ways we could do it in another way. We acquired a VESC controller to compare our
system and a commercial product. Preliminary results demonstrate that the adapted VESC-based controller successfully
drives the target motor under both commutation strategies, and that positional control is achievable with the current
hardware configuration. Security vulnerabilities related to open Bluetooth access were identified. These findings
suggest that open-source, locally fabricated motor controllers can meet the functional requirements of electric cargo
bikes while significantly improving repairability.
\end{abstract}
\begin{IEEEkeywords}
@ -209,8 +210,10 @@ The objective is to minimize the perceived additional effort when towing a cargo
PID-based (ProportionalIntegralDerivative) control strategy combined with distance sensing, allowing adaptive
assistance based on system dynamics.
\section{Hardware-Based Six-Step Commutation Controller}
\section{STM32-Based Field-Oriented Control Motor Drive}
@ -294,9 +297,10 @@ for the the MAD associates.
% ************************************ DYNAMIC MODELLING ***************************************************************
\section{Dynamic Modelling and Control of the BicycleCargo System}
\subsection{System Modelling and Simulation}
\subsection{Dynamic System Modelling}
The studied system consists of a bicycle towing a cargo cart through a rigid mechanical linkage. This link is only used
for steering guidance and does not contribute to the traction force. The main objective is to ensure that the rider
@ -306,8 +310,6 @@ From a control perspective, the rider provides a reference motion in terms of sp
is expected to follow this reference with minimal delay. The position error between the bicycle and the cargo cart is
computed using a distance sensor, which provides feedback relative to an equilibrium state.
\subsubsection{Dynamic Modelling}
The cargo cart is modelled as the plant of the system. Its rotational dynamics are described using the fundamental
equation of rotational motion:
@ -347,15 +349,15 @@ Thus, the transfer function between motor torque and linear velocity is:
\end{equation*}
\subsubsection{Simulation and Control}
\subsection{PI-Based Control Strategy}
\label{subsec:Simulink_model}
Based on this model, a Simulink representation of the system was developed. The controlled system includes a feedback
loop using a PI controller in order to regulate the position error between the bicycle and the cargo cart.
loop using a PI (Proportional-Integral) controller in order to regulate the position error between the bicycle and the cargo cart.
Since the reference input is a ramp signal (representing the bicycle position over time), an integral action is required
to ensure zero steady-state error and accurate tracking of the reference trajectory.
The closed-loop Simulink model of the system is shown in Fig.~\ref{fig:simulink_closedloop}.
The closed-loop Simulink model of the system is shown in Fig.~\ref{fig:simulink-closedloop}.
The control error is defined as the difference between a desired relative position and the measured displacement between
the bicycle and the cargo cart:
@ -363,29 +365,43 @@ the bicycle and the cargo cart:
e(t) = e_{\text{ref}} - (x_{\text{bike}} - x_{\text{cart}})
\end{equation*}
where $e_{\text{ref}} = \SI{-0.5}{\meter}$ represents the desired equilibrium offset between both systems.
The resulting position error between the bicycle and the cargo cart is shown in Fig.~\ref{fig:tracking_error}.
\FloatBarrier
\begin{figure}[!h]
\centering
\includegraphics[width=\linewidth]{./Figures/sys_dyn_matlab.png}
\caption{Closed-loop model of the bicyclecargo system with PI control.}
\label{fig:simulink_closedloop}
\label{fig:simulink-closedloop}
\end{figure}
\subsection{Control Architecture Exploration}
% ******************************** RESULTS **************************************************************************
\section{Results}
\subsection{Bicycle-Cargo System Control Results}
\subsubsection{Simulation Results}
The closed-loop Simulink model presented in the subsection~\ref{subsec:Simulink_model} was used to evaluate the
performance of the proposed PI-based (Proportional-Integral) control strategy.
Figure~\ref{fig:tracking-error} shows the evolution of the tracking error between the bicycle and the cargo cart during
simulation. The response exhibits an initial transient phase followed by a progressive convergence toward the desired
equilibrium position, demonstrating stable closed-loop behaviour and satisfactory tracking performance.
\begin{figure}[!h]
\centering
\includegraphics[width=\linewidth]{./Figures/error_fig.png}
\caption{Position tracking error between bicycle and cargo cart.}
\label{fig:tracking_error}
\label{fig:tracking-error}
\end{figure}
\subsection{Control Architecture Exploration}
\subsubsection{Experimental Load Characterization}
\subsection{Experimental Characterization Under Different Loads}
% ******************************** DISCUSSION **************************************************************************
@ -419,7 +435,6 @@ What should be a clear conclusion from our test with the jammer is that a contro
avoided when possible and practical. Examples where this could be relevant include electric skateboards, as cables could
impose a tripping hazard. There, an encapsulation of an encrypted control frame could be an thought.
\section{Results}
\section{Conclusion/Summary}