Fault Detection, Isolation and Adaptive Augmentation for Incremental Backstepping Flight Control

Abstract

Uncertainties caused by unforeseen malfunctions of the actuator or changes in aircraft behavior could lead to aircraft loss of control during flight. The paper presents a Two-Layer Framework (TLF) augmenting Incremental Backstepping (IBKS) control algorithm designed for an aircraft. IBKS uses angular accelerations and current control deflections to reduce the dependency on the dynamics model. Nevertheless, knowledge of the control effectiveness is still required for proper tracking performance and stability guarantee and becomes essential in a case of failure. The proposed TLF is designed to detect possible problems such as a failure or presence of unknown actuator dynamics and to adapt the control effectiveness. At the first layer, the system performs detection and isolation of possible failures. After a problem being detected and isolated, the algorithm initiates the second-layer adaptation of the individual effectiveness of the failed control effector. For some critical scenarios, when the input-affine property of the IBKS is violated, e.g., for a combination of multiple failures, the IBKS could lose stability. Meanwhile, the proposed TLF-IBKS algorithm has improved tracking and stability performance.