Paraglider & Kite-Based Flight Systems
Automated guidance, stability, and trajectory control — combining control engineering, aerodynamics, and 1,000+ hours of hands-on flight experience.
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Control Challenges
- Highly nonlinear and flexible wing dynamics — far more complex than rigid-body aircraft
- Unstable flight modes requiring active stabilization under turbulence and wind shear
- Limited onboard sensing: no rigid IMU mounting, GPS dropout, unreliable airspeed
- Safety-critical constraints: stall margins, tether tension limits, and structural load factors that must never be violated across the full flight envelope
Focus Areas
Airborne Wind Energy (AWE)
Kite and paraglider-based AWE systems harvest wind at altitudes (200–600 m) inaccessible to conventional turbines. I design trajectory controllers that execute autonomous pumping cycles or continuous crosswind figure-8 patterns, maximizing energy yield while respecting tether tension limits, structural load constraints, and return-to-ground sequences.
Paraglider State Estimation & Flight Control
Designing complete closed-loop flight control systems for paragliders: stability analysis of the nonlinear coupled wing-pilot system, synthesis of stability augmentation controllers, and autonomous trajectory tracking. The work covers the full chain — from sensor fusion and state observer design through to onboard controller deployment — informed by 1,000+ hours of hands-on paraglider flight.
Technical Approach
Nonlinear Flight Dynamics Modeling
Physics-based models for flexible-wing systems — capturing spanwise load distribution, canopy twist, and aerodynamic coupling to give the MPC an accurate prediction model.
Trajectory Optimization
Time- and energy-optimal path planning for autonomous soaring, crosswind energy extraction, and return-to-home manoeuvres, including ground-station tether management for AWE systems.
State Estimation & Observer Design
Reconstruct angle of attack, sideslip, canopy load distribution, and apparent wind by fusing accelerometer, GPS, barometric, and line-tension data through Kalman filter and nonlinear observer designs. The estimated state feeds directly into the flight control loop.
Embedded Real-Time Controllers
Deploy solvers on microcontrollers and embedded flight computers meeting hard real-time budgets required for active flight control and autonomous landing.
Practical Model Development
Models as simple as possible — geometry and basic physics for linear feedback design, a minimal nonlinear extension only when simulation validation requires it. Rarely is more complexity justified.
Read the full modelling approach →Relevant Design Patterns
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I combine deep control engineering expertise with first-hand understanding of paraglider and kite flight dynamics. A 30-minute call is enough to assess your project's feasibility.
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