Immunity-Based Abnormal Condition Accommodation of Aircraft Sub-System Failures

Author(s):  
Adil Togayev ◽  
Mario G. Perhinschi ◽  
Dia Al Azzawi ◽  
Hever Moncayo ◽  
Israel Moguel ◽  
...  

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.

2017 ◽  
Vol 89 (1) ◽  
pp. 164-175 ◽  
Author(s):  
Adil Togayev ◽  
Mario Perhinschi ◽  
Hever Moncayo ◽  
Dia Al Azzawi ◽  
Andres Perez

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.


2011 ◽  
pp. 2152-2174
Author(s):  
Tao Gong

Static Web immune system is an important applicatiion of artificial immune system, and it is also a good platform to develop new immune computing techniques. On the Static Web system, a normal model is proposed with the space property and the time property of each component, in order to identify the normal state of the system that the artificial immune system protects. Based on the normal model, the Static Web immune sytsem is modelled with three tiers, that is the innate immune tier, the adaptive immune tier and the parallel immune tier. All the three tiers are inspired from the natural immune system. On the tri-tier immune model, the self detection mechanism is proposed and programmed based on the normal model, and the non-self detection is based on the self detection. Besides, the recognition of known non-selfs and unknown non-selfs are designed and analyzed. It is showed that the Static Web immune system is effective and useful for both theory and applications.


Author(s):  
Tao Gong

Static Web immune system is an important applicatiion of artificial immune system, and it is also a good platform to develop new immune computing techniques. On the Static Web system, a normal model is proposed with the space property and the time property of each component, in order to identify the normal state of the system that the artificial immune system protects. Based on the normal model, the Static Web immune sytsem is modelled with three tiers, that is the innate immune tier, the adaptive immune tier and the parallel immune tier. All the three tiers are inspired from the natural immune system. On the tri-tier immune model, the self detection mechanism is proposed and programmed based on the normal model, and the non-self detection is based on the self detection. Besides, the recognition of known non-selfs and unknown non-selfs are designed and analyzed. It is showed that the Static Web immune system is effective and useful for both theory and applications.


2014 ◽  
Vol 118 (1205) ◽  
pp. 775-796 ◽  
Author(s):  
M. G. Perhinschi ◽  
H. Moncayo ◽  
B. Wilburn ◽  
J. Wilburn ◽  
O. Karas ◽  
...  

Abstract This paper presents the development and testing through simulation of an integrated scheme for aircraft sub-system failure detection and identification (FDI) based on the artificial immune system (AIS) paradigm augmented with artificial neural networks. The features that define the self within the AIS paradigm include neural estimates of the angular accelerations produced by the abnormal conditions. The simulation environment integrates the NASA Generic Transport Model interfaced with FlightGear. A hierarchical multi-self strategy was investigated for developing FDI schemes capable of handling malfunctions of a variety of aircraft sub-systems. The performance of the FDI scheme has been evaluated in terms of false alarms and successful detection and identification over a wide flight envelope and for several actuator and aerodynamic surface failures. For all cases considered, the performance was very good, confirming the potential of the AIS paradigm augmented with the proposed neural network-based approach for feature definition to offer a comprehensive solution to the aircraft sub-system FDI problem.


2021 ◽  
Vol 1842 (1) ◽  
pp. 012001
Author(s):  
Chairun Nas ◽  
Nursaka Putra ◽  
Yeyi Gusla Nengsih ◽  
Ilwan Syafrinal

Sign in / Sign up

Export Citation Format

Share Document