HarryMann, I've resisted replying to mm43 on that point. Any cogent reply would get too deeply into analysis of digital data and filter theory.
For example: Sensor data of any sort is inherently noisy. Think in terms of turbulence and the way it would randomize data from a pressure detector on a part of the aircraft with turbulent air flow.
You can smooth data which is inherently noisy by filtering it. Depending on the characteristics of the noise from sensors themselves increasing the sample rate might and might not do some good. Note that the sensors themselves will provide some filtering of high frequency noise.
If you filter over several minutes the accuracy of the filter output can be quite good. But that much filtering introduces delay. In point of fact there are two basic types of filters in the digital realm, finite and infinite impulse response.
The infinite impulse response filters resemble pure analog filters. The delay of the filter is directly related to the filter's bandwidth and "shape". The narrower the filter the longer the delay. The same applies to the finite impulse response filters with slightly different constants involved.
The response of a 10 Hz low pass filter of the same design is 10 times slower than a 100 Hz low pass filter. And the output has 10 times the noise power for what is called "White Gaussian Noise" (typical radio noise with no antenna connected.) I have no reason to presume aircraft sensors respond with WGN superimposed on the signals. But it's a starting point for discussion.
I think you can see where this is going. It gets deeper and deeper and nastier as you dig into it. The upshot of it all is that you must determine what response rate is really necessary for keeping the control loops for the aircraft stable while filtering out enough noise that the aircraft is not trying to respond to turbulence that is better damped out by wing design.
I do know that this is an area Rockwell Collins is experimenting with. I saw a video from them some time back that showed an autopilot controlled "model" aircraft lose its wing and continue to fly after a momentary upset. (Of course, if you put enough motor on a brick it will fly. The trick is to get it to go where you want. Ever see pictures of the flying lawn mower?) I figure this is an area where there is still some research needed to find optimums. And it all interacts with the physical characteristics if the aircraft such as wing flexibility and so forth.
So I hesitate to suggest a higher sample rate might be beneficial, unless there is CPU power to burn. (I suspect that was not the case given the year the computers for the A330 series was designed.)
I've rambled too much here. Please excuse me. I hope you learned enough to appreciate some of the problems involved just in filtering data alone.