Yes, it's exactly the same class. You can take any constant size list of parameters and combine them just using addition. This is particularly obvious in Flum and Grohe's formulation of $FPT$ where problems are equipped with a parameterization $\kappa : x \rightarrow \mathbb{N}$.
So for example, you can take a problem with two parameters $k$ and $r$, and produce a combined parameter $k+r$ (or indeed using any moderately sane function), as if the running time is bounded by some function $f(k,r)$ (we can ignore the $|x|^{O*(1)}$ part for the moment)), then it is bounded by the function $f(g(k+r),h(k+r)) = f'(k+r)$, where $g$ and $h$ do whatever is necessary to turn $k+r$ into a sufficiently usable form (in most cases, this is nothing).
Note that this produces the intuition you expect. If $(\Pi,\kappa) \in FPT$, then it is still in $FPT$ when you add a new parameter, however it is not necessarily true that if $(\Pi,\kappa_{1} + \kappa_{2}) \in FPT$ then either $(\Pi,\kappa_{1}) \in FPT$ or $(\Pi,\kappa_{2}) \in FPT$.
As an example, deleting $k$ vertices to obtain an $r$-regular graph is $W[1]$-hard with parameter $k$, $paraNP$-complete with parameter $r$ but in $FPT$ with parameter $k+r$.