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#5630. Wheel-slip estimation for advanced braking controllers in aircraft: Model based vs. black-box approaches
| July 2026 | publication date |
| Proposal available till | 22-05-2025 |
| 4 total number of authors per manuscript | 0 $ |
| The title of the journal is available only for the authors who have already paid for |
| Journal’s subject area: |
| Applied Mathematics; Computer Science Applications; Electrical and Electronic Engineering; Control and Systems Engineering; |
| place 1 | place 2 | place 3 | place 4 |
| Free | Free | Free | Free |
| 2350 $ | 1200 $ | 1050 $ | 900 $ |
Contract №5630.1   | Contract №5630.2 | Contract №5630.3 | Contract №5630.4 |
1 place - free (for sale)
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)
Abstract:
As of today, most aircraft are endowed with Anti-lock Braking Systems that are active during landings and rejected take-off manoeuvres, ensuring the maximum exploitation of road-friction capability. Due to strict certification issues, the braking controller must function using only signals that are local to the landing gear, which is the aircraft sub-system hosting the braking actuators. In the most common scenarios, the only available signals are the wheel speed and the braking pressure. This limited set of information prevents the use of advanced braking control architectures which are now mainstream in the automotive sector, i.e., those based on the regulation of the wheel slip, so that typical aircraft Anti-lock Braking Systems are usually based on the regulation of the wheel deceleration. This paper investigates how a reliable wheel slip estimation can be achieved using wheel speed and braking pressure signals, analysing different wheel slip observers options. In particular, a model-based approach that uses a sliding-mode observer is proposed, together with a black-box approach based on Nonlinear Auto-Regressive models with eXogenous input, with a neural network implementation.
Keywords:
Aircraft; Anti-lock braking control; Neural networks; Sliding mode observer; Wheel slip estimation
Contacts :
2 place - free (for sale)
3 place - free (for sale)
4 place - free (for sale)
Abstract:
As of today, most aircraft are endowed with Anti-lock Braking Systems that are active during landings and rejected take-off manoeuvres, ensuring the maximum exploitation of road-friction capability. Due to strict certification issues, the braking controller must function using only signals that are local to the landing gear, which is the aircraft sub-system hosting the braking actuators. In the most common scenarios, the only available signals are the wheel speed and the braking pressure. This limited set of information prevents the use of advanced braking control architectures which are now mainstream in the automotive sector, i.e., those based on the regulation of the wheel slip, so that typical aircraft Anti-lock Braking Systems are usually based on the regulation of the wheel deceleration. This paper investigates how a reliable wheel slip estimation can be achieved using wheel speed and braking pressure signals, analysing different wheel slip observers options. In particular, a model-based approach that uses a sliding-mode observer is proposed, together with a black-box approach based on Nonlinear Auto-Regressive models with eXogenous input, with a neural network implementation.
Keywords:
Aircraft; Anti-lock braking control; Neural networks; Sliding mode observer; Wheel slip estimation
Contacts :
