RMS value of a signal with a DC offset in MATLAB
RMS values don't simply add up. The RMS value of $N$ discrete samples $x[n]$ (assuming $0\le n&lt;N$) is

$$x_{RMS}=\sqrt{\frac{1}{N}\sum_{n=0}^{N-1}x^2[n]}\tag{1}$$

Now if you have $y[n]=x[n]+c$ with some constant $c$, the RMS value of $y[n]$ is

$$\begin{align}y_{RMS}&amp;=\sqrt{\frac{1}{N}\sum_{n=0}^{N-1}y^2[n]}\\&amp;=\sqrt{\frac{1}{N}\sum_{n=0}^{N-1}(x[n]+c)^2}\\&amp;=\sqrt{\frac{1}{N}\sum_{n=0}^{N-1}(x^2[n]+2cx[n]+c^2)}\\&amp;=\sqrt{\frac{1}{N}\sum_{n=0}^{N-1}x^2[n]+\frac{2c}{N}\sum_{n=0}^{N-1}x[n]+\frac{1}{N}\sum_{n=0}^{N-1}c^2}\tag{2}\end{align}$$

If we define the mean value of $x[n]$ as

$$m_x=\frac{1}{N}\sum_{n=0}^{N-1}x[n]\tag{3}$$

then from $(2)$ the square of the RMS value of $y[n]$ can be expressed as

$$y^2_{RMS}=x^2_{RMS}+2cm_x+c^2\tag{4}$$

So if you assume that the mean of $x[n]$ equals zero, the squares of the RMS values add up:

$$y^2_{RMS}=x^2_{RMS}+c^2\tag{5}$$

You can easily verify Eq. $(5)$ using your example:

$$(282.7014)^2+(200)^2=(346.2948)^2\tag{6}$$