Filter the rpm signal. Depending on what toolboxes you have, there are a lot of tools you could use. I'm just going to use a very rudimentary approach without anything special.
fs= 10000; % sampling frequency
dt = 1/fs;
T = 1; % total time
t = 0:dt:T; % time vector
% a random vector
rpm = randn(length(t),1);
% filter the vector
ft = 0.05; % this scales the filter width
R = floor((ceil((ft*fs*5-1)/2)*2+1)/2); % this is always even
x = -R:R; % so this is always of odd length
fk = exp(-(x/(1.414*ft*fs)).^2); % a 1-D gaussian
rpm = conv(rpm,fk,'same'); % apply LPF
% scale/translate the vector
rpmrange = [1190 1210];
rpmrange0 = [min(rpm) max(rpm)];
rpm = (rpm-rpmrange0(1))/range(rpmrange0); % normalize
rpm = rpm*range(rpmrange) + rpmrange(1); % rescale
% show it
plot(t,rpm); xlabel('s'); ylabel('rpm')
