Immunity-based accommodation of aircraft subsystem failures

Abstract

Immunity-Based Accommodation of Aircraft Subsystem Failures This thesis presents the design, development, and flight-simulation testing of an artificial immune system (AIS) based approach for accommodation of different aircraft subsystem failures. Failure accommodation is considered as part of a complex integrated AIS scheme that contains four major components: failure detection, identification, evaluation, and accommodation. The accommodation part consists of providing compensatory commands to the aircraft under specific abnormal conditions based on previous experience. In this research effort, the possibility of building an AIS allowing the extraction of pilot commands is investigated. The proposed approach is based on structuring the self (nominal conditions) and the non-self (abnormal conditions) within the AIS paradigm, as sets of artificial memory cells (mimicking behavior of T-cells, B-cells, and antibodies) consisting of measurement strings, over pre-defined time windows. Each string is a set of features values at each sample time of the flight including pilot inputs, system states, and other variables. The accommodation algorithm relies on identifying the memory cell that is the most similar to the incoming measurements. Once the best match is found, control commands corresponding to this match will be extracted from the memory and used for control purposes. The proposed methodology is illustrated through simulation of simple maneuvers at nominal flight conditions, different actuators, and sensor failure conditions. Data for development and demonstration have been collected from West Virginia University 6-degreesof-freedom motion-based flight simulator. The aircraft model used for this research represents a supersonic fighter which includes model following adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The simulation results demonstrate the possibility of extracting pilot compensatory commands from the self/non-self structure and the capability of the AIS paradigm to address the problem of accommodating actuator and sensor malfunctions as a part of a comprehensive and integrated framework along with abnormal condition detection, identification, and evaluation. DEDICATION To my mother Gulnara Yezhebayeva and my grandparents,

Partitioned artificial immune system for detection and identification of autonomous flight vehicle abnormal conditions

“…The self/nonself discrimination capabilities of the immunity paradigm have been extended to perform not only AC detection but also identification (Perhinschi et al, 2014b), evaluation Detection of flight vehicle abnormal conditions (Moncayo et al, 2011a) and even AC accommodation (Togayev et al, 2017). Certain levels of self/ nonself structuring is necessary for these processes.…”

Immunity-Based Framework for Autonomous Flight in GPS-Challenged Environment

“…Specific immunity-inspired approaches for abnormal condition detection, identification, evaluation, and accommodation have been developed. In particular, mimicking the capability of the immune system to memorize antigen/antibody correlation was investigated with promising results for aircraft control purposes [60]. The immunity-based monitoring approach was successfully tested with actual UAV flight data [61] and hardware-in-the-loop simulation [62,63].…”

Artificial Immune System for Unmanned Aerial Vehicle Abnormal Condition Detection and Identification

“…Immunity based approaches have also been used for evaluation of aircraft actuator faults [52] over the extended flight envelope [53]. It has also been used for AC accommodation in situations of particular actuator locks [54] and in autonomous flight in a GNSS-denied environment [55]. The engine of the aircraft is another important system where the AIS could be applied.…”