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An aircraft engine control system consists of a large scale of control parameters and variables because of the complex structure of aero-engine. Monitoring and adjusting control variables and parameters such as detecting, isolating and reconfiguring the system faults/failures depend on the controller design. Developing a robust controller is based on an accurate mathematical model.

In this study, a small-scale turboprop engine is modeled. Simulation is carried out on MATLAB/Simulink for design and off-design operating conditions. Both steady-state and transient conditions (from idle to maximum thrust levels) are tested. The performance parameters of compressor and turbine components are predicted via trained Neuro-Fuzzy model (ANFIS) based on component maps. Temperature, rotational speed, mass flow, pressure and other parameters are generated by using thermodynamic formulas and conservation laws. Considering these calculated values, error calculations are made and compared with the cycle data of the engine at the related simulation conditions.

Simulation results show that the designed engine model’s simulation values have acceptable accuracy for both design and off-design conditions from idle to maximum power operating envelope considering cycle data. The designed engine model can be adapted to other types of gas turbine engines.

Different from other literature studies, in this work, a small-scale turboprop engine is modeled. Furthermore, for performance prediction of compressor and turbine components, ANFIS structure is applied.

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.

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.

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

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.

The aviation industry has started environment friendly and also conventional energy independent alternative energy dependent designs to reduce negative impacts on the nature and to maintain its future activities in a clear, renewable and sustainable way. One possible solution proposed is solar energy. Solar-powered aerial vehicles are seen as key solutions to reduce global warming effects. This study aims to simulate a mathematical model of a solar powered DC motor of an UAV on MATLAB/Simulink environment.

Maximum power point tracking (MPPT) is a critical term in photovoltaic (PV) array systems to provide the maximum power output to the related systems under certain conditions. In this paper, one of the popular MPPT techniques, “Incremental Conductance”, is simulated with solar-powered DC motor for an UAV design on MATLAB/Simulink.

The cascade structure (PV cell, MPPT, buck converter and DC motor models) is simulated and tested under various irradiance values, and results are compared to the DC motor technical data. As a result of that, mathematical model simulation results are overlapped with motor technical reference values in spite of irradiance changes.

It is suggested to be used in real time applications for future developments.

Different from other solar-powered DC motor literature works, a solar-powered DC motor mathematical model of an UAV is designed and simulated on MATLAB/Simulink environment. To adjust the maximum power output at the solar cell, incremental conductance MPPT technique is preferred and a buck converter structure is connected between MPPT and DC motor mathematical model. It is suggested to be used in solar-powered UAV designs for future developments.

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.

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.

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.

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

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

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.