If $A$ is a psd matrix, can we say $F(A,T) :=\int_0^T e^{tA}\,dt = (e^{TA}-I)A^\dagger$, where $A^\dagger$ is the Moore-Penrose pseudo-inverse of $A$ ?
Afterall,
- The result holds if $A$ is positive-definite (thanks to the first part of this post https://math.stackexchange.com/a/658289/168758).
- For small $\lambda>0$ can approximate $A$ by a positive-definite matrix $B_\lambda := A+\lambda I$, and it argue that $$ F(A,t) \overset{?}{=} \lim_{\lambda \to 0^+}F(B_\lambda, T) = \lim_{\lambda \to 0^+}(e^{TB_\lambda}-I)B_\lambda^{-1} = (e^{TA}-I)A^\dagger, $$ where the first step is not justified.
The notations $\frac{e^{At}-}{A}$ or $(e^{At} - )A^{-1}$ are typically just used as a (bad) way to abbreviate the series
$$\begin{aligned} \frac{ + At + ½A^2t^2 + … -}{A} = \frac{At(+½At + …)}{A} = t\sum_{k=0}^{∞}\tfrac{(At)^k}{(k+1)!} \end{aligned}$$
which exists even when $A$ is arbitrarily singular. This quantity occurs when solving linear ODEs.
A better notation would be to use the so-called $φ$ functions, which are recursively defined by
$$ φ_m(z) = zφ_{m+1}(z) + \tfrac{1}{m!},φ_0(z) = e^z \quad⇝\quadφ_m(z) = \sum_{k=0}^∞ \frac{z^k}{(k+m)!}$$
For example, the solution to the inhomogeneous linear ODE with constant coefficients
$$ \dot{x}(t) = Ax(t) + b$$
Is given by $x(t+∆t) = e^{A{∆t}}x(t) + φ(A{∆t}){∆t}b$.
More generally, if $b=b(t)$ is time-varying and locally analytical on $U_{∆t}(t)$, then the solution to $\dot{x}(t) = Ax(t) + b(t)$ in this neighbourhood can be expressed as
$$ x(t+∆t) = e^{A{∆t}}x(t) + \sum_{k=1}^{∞}φ_k(A{∆t}) {∆t}^k \frac{^{k-1} b(t)}{ t^{k-1}}$$
References: