Attitude determination and control is a key component of satellite missions, enabling diverse mission capabilities and improving communication with ground operators. Momentum wheels are a common method of providing attitude control on small satellite platforms, and the reliability of the motors driving the wheels is critical for the continued operation of satellite pointing capabilities. As the motors degrade over time, the pointing accuracy decreases and the satellite loses controllability. Loss of pointing capabilities is a terminal, single-point failure for many missions. Momentum wheel control requires a minimum of four wheels, while a reaction wheel setup requires three wheels; consequently, a four-wheel system can be designed to be robust to a single motor failure if there is a way to detect which motors remain operational. It is advantageous to autonomously monitor motor health to detect degradation and failure for real-time on-orbit recovery to maximize attitude control lifetime and thereby extend mission capabilities. The on-orbit application imposes limitations on available data and computational resources, specifically constraining computational complexity and data rates. This work proposes a custom detector based on the requirements specific to attitude control that does not require training a detector for general failure mechanisms. There are two key modes that describe motor degradation which impact pointing performance: efficiency and precision. The first mode, efficiency, is the power required to drive the motor at a given speed. Efficiency is monitored using the mean of the applied current normalized by the commanded speed. The second mode, precision, is the error between commanded speed and actual speed. Error is monitored using the difference between the measured and commanded speeds. In the proposed detector, these two parameters are monitored to assess the health of the motor, from which control parameters can be set. This algorithm can run onboard with minimal impact and does not require the high data rates associated with frequency-domain detection methods. The algorithm is demonstrated on a dataset from a motor lifetime test, during which motors experienced healthy, degraded, and failure modes. A method for implementing the algorithm is discussed, and recommendations for future work are provided.


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    Title :

    Real-Time On-Orbit Momentum Wheel Health Monitoring for Robust Satellite Attitude Control


    Contributors:


    Publication date :

    2021-03-06


    Size :

    1206599 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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