Client
PhD researchers - ETH
Client Requirements
To address the limitation of attitude recovery in traditional twin-rotor aircraft—caused by fixed centers of gravity (COG) under unstructured disturbances—the client sought an innovative hardware structure and control algorithm. The goal was to achieve efficient and stable transitions across multiple modes, including hover, morphing/tilting, and cruise.
Our Answer
Starting from improved system dynamics, we developed two integrated hardware and algorithmic solutions:
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Bio-inspired Adaptive Tail: Inspired by the flight mechanics of Odonata (dragonflies), we developed a 3-DOF bio-inspired tail system. By dynamically adjusting the COG, it generates a maximum compensation torque of 0.3N·m, increasing attitude response speed by 35%.
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Auxiliary Thrust Vectoring: Introduced auxiliary axial vector propellers supporting a 0°–90° thrust vectoring range. Combined with Nonlinear Model Predictive Control (NMPC), this effectively suppressed disturbances in the 0.5–5 Hz frequency band.
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Intelligent Control Architecture: Utilized Reinforcement Learning (RL) to pre-train flap deflection strategies for various scenarios. This ensures that the aircraft maintains quadrotor-level control robustness during the wing-tilting morphing phase.
