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→How to get the data for sensor characteristics?
== Which characteristics will be modeled? ==
Some basic characteristics are: <ref>Sensors – the first chain in the measurement chain by Kim R. Fowler and John L. Schmalzel.</ref>
* '''Bias:''' Due to temperature dependence or manufacturing defect the output is not zero at zero input. This is known as bias.
* '''Noise:''' Signals which can't be measured are known as noise.
== Will the above model would be enough for control law design? ==
For a preliminary model and for most practical purposes, this would be enough. However, one can dig into the physics of the particular sensor, write transfer function for each of the details, to get some more characteristics such as lag etc. <ref>A simple MEMS gyro model using MATLAB / Simulink: https://www.youtube.com/watch?v=P1OEoA70YJo</ref><br \>
One can also think about what causes error in the actual value and measured values. For example, mounting of the sensor improperly would produce erroneous result. Change of temperature or surrounding electric/magnetic field can be sometimes problematic. These can be incorporated in the model to make it more accurate.
== How to get the data for sensor characteristics? ==
One can get these data from the sensor datasheet. You can get the datasheet from the supplier site of the sensor or else Google the model number and type of sensor. Read only the datasheet from the manufacturer and make sure that your model is the same as the model in the datasheet. Do not underestimate the reading of datasheet, it takes quite lot of effort to understand it properly. Sometimes the units of a parameter in the datasheet will help in understanding it. <br \> <br \>----
If you are done reading this page, you can go back to [[Attitude Determination and Control Subsystem]]
==References ==