An adaptive threshold approach for the design of an actuator failure detection and identification scheme

Typical logic schemes associated with failure detection and identification algorithms rely on a set of constant thresholds. The selection of the values for these thresholds is generally a tradeoff between the goals of maximizing failure detectability while minimizing false alarm rates. The main purpose of this brief is to propose an alternative to this conventional approach for defining the thresholds of a specific aircraft actuator failure detection and identification scheme. A specific set of detection and identification criteria for failures of the decoupled stabilators, canards, ailerons, and rudders of the NASA Advanced Control Technology for Integrated Vehicle F-15 aircraft have been formulated in terms of neural network estimates and correlation functions of the angular rates. The proposed scheme is based on the use of adaptive thresholds through the floating limiter concept. This new approach eliminates the need for parameter scheduling and has shown to be able to reduce the delays associated with the constant threshold method. The functionality of the approach has been illustrated through numerical simulations on the West Virginia University NASA Intelligent Flight Control System F-15 simulator.