New fuzzy-RNN autopilot system Cessna is a M.Tech project topic for Aerospace Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
New fuzzy-RNN autopilot system Cessna Project Details
| Abstract |
This paper proposes the first fully autonomous artificial intelligence (AI) based autopilot system to manage the longitudinal flight of the Cessna Citation X (CCX) aircraft during cruise flight. The approach uses two multiplayer fuzzy recurrent neural networks (MFRNNs) to model the unknown dynamics of the aircraft for vertical speed (VS) and altitude hold (AH) mode dynamic state-space representations. These MFRNNs are trained online using a hybrid swarm optimization and backpropagation training approach. For each mode, two sliding mode controllers (SMC) are configured to ensure robustness. Also, a new fuzzy logic algorithm is implemented for smooth and efficient changes for the autopilot modes. The performance of the system is evaluated through
a nonlinear simulation platform of the CCX, using the data from a FAA Level D certified flight simulator. The Lyapunov theorem demonstrates the stability and robustness of the system. The controllers demonstrate excellent tracking performance with uncertainty during turbulence and 925 different flight conditions (including turbulent and non-turbulent) of the aircraft during flight testing.
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| Reference Paper |
New fuzzy-RNN autopilot system for the Cessna Citation X aircraft with a fuzzy transition algorithm |
| Domain |
Aerospace Engineering |
| Sub-Domain |
Structures & Systems / Guidance Navigation Control / Autopilot Design |
| PDF Download |
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| Get Help |
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