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This paper presents a detection system which generate an alarm if exist an anomaly state in the stability control system of an aircraft. A servo type controller with integrator for the regulation of the Roll, Pitch and Yaw was designed starting from the lateral longitudinal and dimensional model. The models are excited with steps of random sizes and disturbed with different random signals to generate the database of suitable and non-suitable states. Radial base classifiers were trained and validated for its use in the detection of anomalous behaviors that may occur in the aircraft stability. The accuracy obtained with the classifiers was greater than the 93.33% for all the variables studied, indicating that classification techniques used, offer reliability in the determination of anomalous States in the simulation of the flight of the aircraft and that could be used in reall flights [ABSTRACT FROM AUTHOR]