Typo <noupdate>

src/year2/distributed-autonomous-systems/sections/_formation_control.tex

@@ -5,7 +5,7 @@
 
 \begin{description}
     \item[Mass-spring system] \marginnote{Mass-spring system}
-        System of $N$ masses where each mass $i$ has a position $x_i \in \mathbb{R}$ and is connected through a sprint to mass $i-1$ and $i+1$. Each spring has an elastic constant $a_{j, i} = a_{i, j} > 0$.
+        System of $N$ masses where each mass $i$ has a position $x_i \in \mathbb{R}$ and is connected through a spring to mass $i-1$ and $i+1$. Each spring has an elastic constant $a_{j, i} = a_{i, j} > 0$.
 
         \begin{figure}[H]
             \centering

src/year2/distributed-autonomous-systems/sections/_optimization.tex

@@ -611,7 +611,7 @@
 
 \begin{description}
     \item[Distributed gradient algorithm] \marginnote{Distributed gradient algorithm}
-        Method that estimates a (more precise) set of parameters as a weighted sum those of its neighbors' (self-loop included):
+        Method that estimates a (more precise) set of parameters as a weighted sum of those of its neighbors' (self-loop included):
         \[ 
             \vec{v}_i^{k+1} = \sum_{j \in \mathcal{N}_i} a_{ij} \z_j^k 
         \]

src/year2/distributed-autonomous-systems/sections/_safety_controllers.tex

@@ -9,7 +9,7 @@
         \]
         with $\x(t) \in \mathbb{R}^n$, $\u(t) \in U \subseteq \mathbb{R}^m$, $f(\x(t)) \in \mathbb{R}^n$, and $g(\x(t)) \in \mathbb{R}^{n \times m}$.
 
-        $f(\x(t))$ can be seen as the drift of the system and $\u(t)$ a coefficient that controls how much $g(\x(t))$ is injected into $f(\x(t))$.
+        $f(\x(t))$ can be seen as the drift of the system and $\u(t)$ as a coefficient that controls how much $g(\x(t))$ is injected into $f(\x(t))$.
 
         The overall system can be interpreted as composed of:
         \begin{itemize}