Mario Perhinschi, Dia Al Azzawi, Hever Moncayo, Andres Perez and Adil Togayev
This paper aims to present the development of prediction models for aircraft actuator failure impact on flight envelope within the artificial immune system (AIS) paradigm.
Abstract
Purpose
This paper aims to present the development of prediction models for aircraft actuator failure impact on flight envelope within the artificial immune system (AIS) paradigm.
Design/methodology/approach
Simplified algorithms are developed for estimating ranges of flight envelope-relevant variables using an AIS in conjunction with the hierarchical multi-self strategy. The AIS is a new computational paradigm mimicking mechanisms of its biological counterpart for health management of complex systems. The hierarchical multi-self strategy consists of building the AIS as a collection of low-dimensional projections replacing the hyperspace of the self to avoid numerical and conceptual issues related to the high dimensionality of the problem.
Findings
The proposed methodology demonstrates the capability of the AIS to not only detect and identify abnormal conditions (ACs) of the aircraft subsystem but also evaluate their impact and consequences.
Research limitations/implications
The prediction of altered ranges of relevant variables at post-failure conditions requires failure-specific algorithms to correlate with the characteristics and dimensionality of self-projections. Future investigations are expected to expand the types of subsystems that are affected and the nature of the ACs targeted.
Practical implications
It is expected that the proposed methodology will facilitate the design of on-board augmentation systems to increase aircraft survivability and improve operation safety.
Originality/value
The AIS paradigm is extended to AC evaluation as part of an integrated and comprehensive health management process system, also including AC detection, identification and accommodation.
Details
Keywords
Adil Togayev, Mario Perhinschi, Hever Moncayo, Dia Al Azzawi and Andres Perez
This paper aims to describe the design, development and flight-simulation testing of an artificial immune-system-based approach for accommodation of different aircraft sub-system…
Abstract
Purpose
This paper aims to describe the design, development and flight-simulation testing of an artificial immune-system-based approach for accommodation of different aircraft sub-system failures/damages.
Design/methodology/approach
The approach is based on building an artificial memory, which represents self- (nominal conditions) and non-self (abnormal conditions) within the artificial immune system paradigm. Self- and non-self are structured as a set of memory cells consisting of measurement strings, over pre-defined time windows. Each string is a set of features values at each sample time of the flight. The accommodation algorithm is based on the cell in the memory that is the most similar to the in-coming measurement. Once the best match is found, control commands corresponding to this match are extracted from the memory and used for control purposes.
Findings
The results demonstrate the possibility of extracting pilot compensatory commands from the self/non-self structure and capability of the artificial-immune-system-based scheme to accommodate an actuator malfunction, maintain control and complete the task.
Research limitations/implications
This paper concentrates on investigation of the possibility of extracting compensatory pilot commands. This is a preliminary step toward a more comprehensive solution to the aircraft abnormal condition accommodation problem.
Practical implications
The results demonstrate the effectiveness of the proposed approach using a motion-based flight simulator for actuator and sensor failures.
Originality/value
This research effort is focused on investigating the use of the artificial immune system paradigm for control purposes based on a novel methodology.