Proving existence of coefficients minimizing $\|y - a_1 x_1 - a_2 x_2 - \ldots - a_n x_n\|$ I'm having quite a bit of difficulty with the following problem from Luenberger's Optimization With Vector Space Methods:

2.9: Let $X$ be a normed linear space and let $x_1, x_2, \ldots, x_n$ be linearly independent vectors from $X$. For fixed $y\in X$, show that there are coefficients $a_1, a_2, \ldots, a_n$ minimizing $\|y - a_1 x_1 - a_2 x_2 - \ldots - a_n x_n\|$.

We're told earlier in the chapter that "an upper semicontinuous functional on a compact subset $K$ of a normed linear space $X$ achieves a maximum on $K$." So I started by considering the functional be $f:\mathbb{R}^n \to \mathbb{R}$ where:
$$f(a; x_1, x_2, \ldots, x_n, y) = \|y - a_1 x_1 - a_2 x_2 - \ldots - a_n x_n\|$$
and $a = (a_1, a_2, \ldots, a_n)$. Then, I was hoping to show that $f$ is lower semicontinuous in $a$ and that the function could be restricted to some compact subset $K$ of $\mathbb{R}^n$.
[Question 1: can I just say that I'm only considering $a_1, a_2, \ldots, a_n$ in some set with a given diameter, i.e., just assume that it is totally bounded?]
For the first part, I want to show that $f$ is lower semicontinuous at $a\in K$, so I'm trying to choose $\delta$ so that for those $b\in K$ for which $\|a - b\| < \delta$ the difference between $f(b)$ and $f(a)$ is less than $\epsilon$. The difference is:
\begin{align}f(b) - f(a) &= \|y - \sum_{i=1}^n b_i x_i\| -\|y - \sum_{i=1}^n a_i x_i\|   \\ &\leq\|\sum_{i=1}^n (a_i - b_i) x_i\| \leq (\max \|x_i\|)\|\sum_{i=1}^n (a_i - b_i)\|\end{align}
At this point, I get stuck as to how $\delta$ fits into the second term. One route I tried was letting $\delta = n\max_i |a_i - b_i|$, but I wasn't sure if I could restrict $b_i$ in this manner. I'd also somehow landed on $\delta < \frac{\epsilon\sqrt{n}}{n \max_i \|x_i\|}$, but this didn't seem to work either.
[Question 2: I feel like I'm missing something obvious here, but any tips on showing that this is LSC?]
Also, a more minor question, do you have any advice on how to write this out properly? I apologize it's so messy.
 A: After spending more time on the problem, here's what I was able to come up with. I'd appreciate any corrections you could provide:
Let $a = (a_1, a_2, \ldots, a_n)$ and $f: \mathbb{R}^n \to \mathbb{R}$ where $f(a, x_1, x_2, \ldots, x_n, y) = \|y - a_1 x_1 - a_2 x_2 - \ldots - a_n x_n\|$. When $x_1, x_2, \ldots, x_n, y$ are evident or irrelevant, I'll write this as $f(a)$.
If $y$ is in the subspace generated by $x_1, x_2, \ldots, x_n$ then there exist unique coefficients satisfying $f(a) = 0$. Otherwise, because $f(0) = \|y\|$, we can limit attention to coefficients satisfying $f(a) \leq \|y\|$, given by $K = \{a\in \mathbb{R}^n: 0 \leq f(a) \leq \|y\|\}$, where $K$ is bounded below by zero and bounded above by $\|y\|$. To show that $K$ is closed, choose $b \in K^c$ so $\|y - \sum b_i x_i\| > \|y\|$. Then, choosing $\epsilon = \frac{\|y - \sum b_i  x_i\| - \|y\|}{\max\|x_i\|}$, if $c\in N_\epsilon(b)$ then $\|y - \sum c_i x_i\| > \|y\|$, meaning that $c\in K^c$ and $K^c$ is open and $K$ is closed. Because $K$ is a subset of Euclidean space and it is closed and bounded, it is compact.
Could someone please double-check the proof that $K$ is open, if possible?
We're told earlier in the chapter that "an upper semicontinuous functional on a compact subset $K$ of a normed linear space $X$ achieves a maximum on $K$." Because we want to prove that $f$ attains a minimum over $K$, we must show that $f$ is lower semicontinuous. Given $\epsilon > 0$, suppose $\|a-b\| < \epsilon/ \max \|x_i\|$. Then
\begin{align}
\epsilon > (\max \|x_i\|)\|a - b\|  &\geq  (\max \|x_i\|)\|\sum_{i=1}^n (a_i - b_i)\| \geq  \|\sum_{i=1}^n (a_i - b_i) x_i\| \\
& \geq \|y - \sum_{i=1}^n b_i x_i\| -\|y - \sum_{i=1}^n a_i x_i\| \geq f(b) - f(a)
\end{align}
and so $f(a) - f(b) < \epsilon$ as desired. Note that $\max \|x_i\| > 0$, since the vectors are independent. Because $f$ is lower semicontinuous over the compact subset $K$, it attains a minimum over the subset.
