Rejection of external disturbances is vital for small aircraft flying in environments with dynamic flow fields, especially due to their increased sensitivity to disturbances. Fixed wing vehicles are generally controlled using successive closure of position and velocity state feedback loops. The successive loop closure method ignores aerodynamic coupling and fails in the presence of strong gusts or aircraft damage. Existing multi-input, multi-output (MIMO) control methods may include aerodynamic coupling and provide more robust performance, but still respond slowly to high speed gusts because they feed back lower order states such as position and velocity. This study aims to develop a MIMO control methodology to feed back translational and rotational acceleration states on a simulated fixed wing aircraft, enabling quicker rejection of disturbances. The novelty of this research is in using these acceleration states in inner feedback loops in addition to the existing autopilot to demonstrate disturbance rejection on a fixed wing vehicle before propagation to lower order states. Using the Ttwistor small Unmanned Aircraft System (sUAS) model and robust control analysis tools, we perform nonlinear flight simulations with and without acceleration feedback and quantify the improvement in disturbance rejection. The resulting augmented autopilot enables the small fixed wing UAS to fly through turbulent, gusty environments by improving disturbance rejection up to 61% in some aircraft states. The improvements shown with the Ttwistor model demonstrate the potential of this method for gust rejection on smaller and more responsive platforms.
Acceleration feedback control for fixed-wing sUAS
2018-03-01
3203370 byte
Conference paper
Electronic Resource
English
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