Any eigenvector corresponding to eigenvalue 2 must satisfy
[tex]\begin{bmatrix}2 & -1 & 0 \\0 & 2 & -2 \\ 0 & 0 & 2\end{bmatrix}\begin{bmatrix}x \\ y \\ z \end{bmatrix}[/tex]
[tex]= \begin{bmatrix}2a- b & 2b- 2c & 2c\end{bmatrix}=\begin{bmatrix} 2x \\ 2y \\ 2z\end{bmatrix}[/tex]
So we have 2a- b= 2a, 2b- 2c= 2b, and 2c= 2c. The first says that b= 0 and the second that c= 0. All eigenvectors are multiples of [tex]\begin{bmatrix}1 \\ 0 \\ 0\end{bmatrix}[/tex].
The characteristic equation for this operator is [itex](\lambda- 2)^3= 0[/itex] and, since a matrix always satifies its own characteristic equation, we must have [itex](T- 2I)^3v= 0[/itex] for all vectors v. Of course if Tv= 2v, that is if v is an eigenvector, the (T- 2I)v= 0 so [itex](T- 2I)^3v= 0[/itex]. But the eigenvectors for this T only span a one-dimensional subspace.
We need to find v such that (T-I)v is not 0 but is in that eigen-space: then we would have [itex](T- I)^2((T-I)v)= (T-I)^2v= 0[/itex]- a "generalized eigenvector".
That is, we look for x, y, z such that
[tex]\begin{bmatrix}0 & -1 & 0 \\ 0 & 0 & -2 \\ 0 & 0 & 0\end{bmatrix}\begin{bmatrix} x \\ y \\ z \end{bmatrix}[/tex][tex]= \begin{bmatrix} -y \\ -2z \\ 0 \end{bmatrix}= \begin{bmatrix}1 \\ 0 \\ 0\end{bmatrix}[/tex].
It is easy to see that
[tex]\begin{bmatrix}0 \\ -1 \\ 0\end{bmatrix}[/tex]
works.
But now we need a vector such that neither (T- 2I)v= 0 nor [itex](T- 2I)^2v= 0[/itex] but such that [itex](T- 2I)^3v= 0[/itex]. Now we need [itex](T- 2I)^2v[/itex] to be an eigenvector which will be the case if
[tex]\begin{bmatrix}0 & -1 & 0 \\ 0 & 0 & -2 \\ 0 & 0 & 0\end{bmatrix}\begin{bmatrix}x \\ y \\ z\end{bmatrix}[/tex][tex]= \begin{bmatrix}-y \\ -2z \\ 0\end{bmatrix}= \begin{bmatrix}0 \\ -1 \\ 0\end{bmatrix}[/tex]
That gives
[tex]\begin{bmatrix}0 \\ 0 \\ \frac{1}{2}\end{bmatrix}[/tex]
Those three vectors form the basis. If P is the matrix having those vectors as columns, then [itex]P^{-1}TP[/itex] will be in Jordan Normal Form.