System Identification and Control Law Optimization Applied to the AeroVironment Quantix Tail-Sitter UAS

Model-based control system design enables aircraft performance metrics and requirements to be directly designed and evaluated for as part of the control system optimization process. The collaborative effort discussed in this paper between AeroVironment and the US Army Aviation Development Directorate (ADD) examines optimizing the control system of the AeroVironment Quantix™ tail-sitter UAS for turbulence rejection. Both the inner, stabilizing loop as well as the outer, velocity command loop are optimized. A higher turbulence rejection capability in hover would increase the maximum allowable wind-speed for take-off and would help ensure the aircraft can safely fly its mission. First, a flight-dynamics model is identified and validated from flight data. A turbulence model is next identified from flight data taken in various turbulence levels and is used to drive performance requirements in the control system optimization process. Flight tests with the optimized control system were conducted to validate anticipated behavior.