Abstract
This paper describes the design, development, and flight-simulation testing of an artificial immune-system-based approach for accommodation of different aircraft sub-system failures/damages. The accommodation of abnormal flight conditions is regarded as part of a complex integrated artificial immune system scheme, which consists of four major components: detection, identification, evaluation, and accommodation. The accommodation part consists of providing compensatory commands under upset conditions for specific maneuvers.
The approach is based on building an artificial memory, which represents the self (nominal conditions) and the 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 including pilot inputs, system states, and other variables. 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 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 and under locked actuator.
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.
Original language | American English |
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DOIs | |
State | Published - Oct 22 2014 |
Externally published | Yes |
Event | ASME 2014 Dynamic Systems and Control Conference - San Antonio, TX Duration: Oct 22 2014 → … |
Conference
Conference | ASME 2014 Dynamic Systems and Control Conference |
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Period | 10/22/14 → … |
Keywords
- Aircraft
- Failure
Disciplines
- Aeronautical Vehicles
- Systems Engineering and Multidisciplinary Design Optimization