Neural network augmented anti-skid controller for transport aircraft

Ilker Tunay, Massoud Amin, Ervin Rodin

Research output: Contribution to conferencePaperpeer-review

2 Scopus citations


This paper describes the design and simulation testing of an anti-skid brake controller for brake-by-wire systems of transport aircraft. The proposed design is based on on-line identification of the friction properties of the runway-tire interface, achieved by combining a multilayer perceptron neural network with fast parameter estimation. We employ recent results from robust control theory to guarantee stability of the whole system despite large uncertainties on the hydraulic components and the brake torque function. In contrast to most commercially available anti-skid controllers, the control signal is smooth, does not result in pressure build-dump cycles and keeps the wheel slip below the tread adhesion limit, thereby potentially reducing tire wear, in addition to improving stopping efficiency.

Original languageEnglish (US)
StatePublished - Jan 1 1999
Externally publishedYes
Event37th Aerospace Sciences Meeting and Exhibit, 1999 - Reno, United States
Duration: Jan 11 1999Jan 14 1999


Other37th Aerospace Sciences Meeting and Exhibit, 1999
Country/TerritoryUnited States


  • Aircraft brakes
  • Anti-lock
  • Anti-skid
  • Hydraulic control
  • Neural network applications
  • Stability robustness


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