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Article
Publication date: 2 May 2017

Isil Yazar, Fikret Caliskan and Emre Kiyak

Condition monitoring and health management of an aircraft engine is of importance due to engine’s critical position in aircraft. Missions require uninterrupted and safer…

290

Abstract

Purpose

Condition monitoring and health management of an aircraft engine is of importance due to engine’s critical position in aircraft. Missions require uninterrupted and safer conditions during the flight or taxi operations. Hence, the deviations, abnormal situations or failures have to be under control. This paper aims to propose a cascade connected approach for an aircraft engine fault tolerant control.

Design/methodology/approach

The cascade connected structure includes a full-order unknown input observer for fault detection and eliminating the unknown disturbance effect on system, a generalized observer scheme for fault isolation and a Boolean logic mechanism for decision-making in reconfiguration process, respectively. This combination is simulated on a linear turbojet engine model in case of unknown input disturbance and under various sensor failure scenarios.

Findings

The simulation results show that the suggested fault detection isolation reconfiguration (FDIR) approach works effectively for multiple sensor failures with various amplitudes.

Originality/value

Different from other studies, the proposed model is sensitive to unknown input disturbance and failures that have unknown amplitudes. One another notable feature of suggested FDIR approach is adaptability of structure against multiple sensor failures. Here, it is assumed that only a single fault is to be detected and isolated at a time. The simulation results show that the proposed structure can be suggested for linear models especially for physical redundancy-based real-time applications easily, quickly and effectively.

Details

Aircraft Engineering and Aerospace Technology, vol. 89 no. 3
Type: Research Article
ISSN: 1748-8842

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Article
Publication date: 5 March 2018

Isil Yazar, Emre Kiyak, Fikret Caliskan and T. Hikmet Karakoc

This paper aims to present a nonlinear mathematical model of a small-scale turbojet aeroengine and also a speed controller design that is conducted for the constructed nonlinear…

538

Abstract

Purpose

This paper aims to present a nonlinear mathematical model of a small-scale turbojet aeroengine and also a speed controller design that is conducted for the constructed nonlinear mathematical model.

Design/methodology/approach

In the nonlinear mathematical model of the turbojet engine, temperature, rotational speed, mass flow, pressure and other parameters are generated using thermodynamic equations (e.g. mass, energy and momentum conservation laws) and some algebraic equations. In calculation of the performance parameters, adaptive neuro fuzzy inference system (ANFIS) method is preferred in related components. All calculated values from the mathematical model are then compared with the cycle data of the turbojet engine. Because of the single variable control need and effect of noise factor, modified proportional–integral–derivative (PID) controller is treated for speed control. For whole operation envelope, various PID structures are designed individually, according to the operating points. These controller structures are then combined via gain-scheduling approach and integrated to the nonlinear engine model. Simulations are performed on MATLAB/Simulink environment for design and off-design operating points between idle to maximum thrust levels.

Findings

The cascade structure (proposed nonlinear engine aero-thermal model and speed controller) is simulated and tested at various operating points of the engine and for different transient conditions. Simulation results show that the transitions between the operating points are found successfully. Furthermore, the controller is effective for steady-state load changes. It is suggested to be used in real-time engine applications.

Research limitations/implications

Because of limited data, only speed control is treated and simulated.

Practical implications

It can be used as an application in the industry easily.

Originality/value

First point of novelty in the paper is in calculation of the performance parameters of compressor and turbine components. ANFIS method is preferred to predict performance parameters in related components. Second novelty in the paper can be seen in speed controller design part. Because of the single variable control need and effect of noise factor, modified PID is treated.

Details

Aircraft Engineering and Aerospace Technology, vol. 90 no. 2
Type: Research Article
ISSN: 1748-8842

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Article
Publication date: 1 April 2005

Chingiz Hajiyev and Fikret Caliskan

The purpose of the paper is to present an approach to detect and isolate the aircraft sensor and control surface/actuator failures affecting the mean of the Kalman filter…

1826

Abstract

Purpose

The purpose of the paper is to present an approach to detect and isolate the aircraft sensor and control surface/actuator failures affecting the mean of the Kalman filter innovation sequence.

Design/methodology/approach

The extended Kalman filter (EKF) is developed for nonlinear flight dynamic estimation of an F‐16 fighter and the effects of the sensor and control surface/actuator failures in the innovation sequence of the designed EKF are investigated. A robust Kalman filter (RKF) is very useful to isolate the control surface/actuator failures and sensor failures. The technique for control surface detection and identification is applied to an unstable multi‐input multi‐output model of a nonlinear AFTI/F‐16 fighter. The fighter is stabilized by means of a linear quadratic optimal controller. The control gain brings all the eigenvalues that are outside the unit circle, inside the unit circle. It also keeps the mechanical limits on the deflections of control surfaces. The fighter has nine state variables and six control inputs.

Findings

In the simulations, the longitudinal and lateral dynamics of an F‐16 aircraft dynamic model are considered, and the sensor and control surface/actuator failures are detected and isolated.

Research limitations/implications

A real‐time detection of sensor and control surface/actuator failures affecting the mean of the innovation process applied to the linearized F‐16 fighter flight dynamic is examined and an effective approach to isolate the sensor and control surface/actuator failures is proposed. The nonlinear F‐16 model is linearized. Failures affecting the covariance of the innovation sequence is not considered in the paper.

Originality/value

An approach has been proposed to detect and isolate the aircraft sensor and control surface/actuator failures occurred in the aircraft control system. An extended Kalman filter has been developed for the nonlinear flight dynamic estimation of an F‐16 fighter. Failures in the sensors and control surfaces/actuators affect the characteristics of the innovation sequence of the EKF. The failures that affect the mean of the innovation sequence have been considered. When the EKF is used, the decision statistics changes regardless the fault is in the sensors or in the control surfaces/actuators, while a RKF is used, it is easy to distinguish the sensor and control surface/actuator faults.

Details

Aircraft Engineering and Aerospace Technology, vol. 77 no. 2
Type: Research Article
ISSN: 0002-2667

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Article
Publication date: 1 February 2005

Rahmi Aykan, Chingiz Hajiyev and Fikret Çalişkan

The purpose of this paper is to maintain safe flight and to improve existing deicing (in‐flight removal of ice) and anti‐icing (prevention of ice accretion) systems under…

1350

Abstract

Purpose

The purpose of this paper is to maintain safe flight and to improve existing deicing (in‐flight removal of ice) and anti‐icing (prevention of ice accretion) systems under in‐flight icing conditions.Design/methodology/approach – A recent academic research on aircraft icing phenomenon is presented. Several wind tunnel tests of an experimental aircraft provided by NASA are used in the neural network training. Five ice‐affected parameters are chosen in the light of these experiments and researches. An offline artificial neural network is used as an identification technique. The Kalman filter is used to increase the state measurement's accuracy such that neural network training performance gets better. A linear A340 dynamic model is selected in cruise conditions. This linear model is simulated in time varying manner in terms of changing icing parameters in a system dynamic matrix. The obtained data are used in neural network training and testing.Findings – Airframe icing can grow in many ways and many points on aircraft. In this research, wing leading edge ice occurrence is only considered at the same level in both left and right wings. During ice growth other faults or anomalies are ignored.Originality/value – Existing icing sensors can only provide an indication about possible ice presence. They cannot give information of the exact level of ice. However, the efficiency of current control system of changed model decreases. The proposed technique offers a method to find out the model changes under icing conditions.

Details

Aircraft Engineering and Aerospace Technology, vol. 77 no. 1
Type: Research Article
ISSN: 0002-2667

Keywords

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