From 27cd819c95538ee41dd57ce1d77779930395f759 Mon Sep 17 00:00:00 2001
From: Francis Gagnon <34136215+franckgaga@users.noreply.github.com>
Date: Mon, 5 Jan 2026 11:32:13 -0500
Subject: [PATCH] Enhance README.md with emoji section headers

Updated section headers in README.md to include emojis for better visual appeal.
---
 README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index a8edc0ef6..b4f7167a0 100644
--- a/README.md
+++ b/README.md
@@ -14,7 +14,7 @@ for the linear systems, [`JuMP.jl`](https://github.com/jump-dev/JuMP.jl) for the
 optimization and [`DifferentiationInterface.jl`](https://github.com/JuliaDiff/DifferentiationInterface.jl)
 for the derivatives.
 
-## Installation
+## 🛠️ Installation
 
 To install the `ModelPredictiveControl` package, run this command in the Julia REPL:
 
@@ -22,7 +22,7 @@ To install the `ModelPredictiveControl` package, run this command in the Julia R
 using Pkg; Pkg.add("ModelPredictiveControl")
 ```
 
-## Getting Started
+## 🚀 Getting Started
 
 To construct model predictive controllers (MPCs), we must first specify a plant model that
 is typically extracted from input-output data using [system identification](https://github.com/baggepinnen/ControlSystemIdentification.jl).
@@ -71,7 +71,7 @@ plot(res, plotry=true, plotymax=true)
 See the [manual](https://JuliaControl.github.io/ModelPredictiveControl.jl/stable/manual/linmpc/)
 for more detailed examples.
 
-## Features
+## ✨ Features
 
 ### 🎯 Model Predictive Control Features