FWAV-Sim is a high-fidelity Unity simulation framework for flapping-wing vehicles that integrates blade-element aerodynamics with bluff-body drag, spatiotemporally correlated fractal turbulence, and realistic IMU/LiDAR/RGB sensor models to support autonomy development.
Hajj, and Ali Nayfeh
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ReLU neural networks approximate transformed constraints in flat systems as unions of polytopes, enabling mixed-integer programming for guaranteed constraint satisfaction in CLF-based and MPC designs for nonlinear systems.
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A Simulation Platform for Flapping-Wing Vehicles
FWAV-Sim is a high-fidelity Unity simulation framework for flapping-wing vehicles that integrates blade-element aerodynamics with bluff-body drag, spatiotemporally correlated fractal turbulence, and realistic IMU/LiDAR/RGB sensor models to support autonomy development.
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An ANN-Enhanced Approach for Flatness-Based Constrained Control of Nonlinear Systems
ReLU neural networks approximate transformed constraints in flat systems as unions of polytopes, enabling mixed-integer programming for guaranteed constraint satisfaction in CLF-based and MPC designs for nonlinear systems.