This article described project of fuzzy logic controller witch control the scope of opening cowl flaps in Piper Seneca V engines. This allows to maintain optimum engine temperature by varying the amount of air flow through the engine compartment. The main task of controller is to reduce pilot workload during the entire flight, as well as to maintain optimum engine operating parameters in order to increase its service life. The designed fuzzy controller generates a cowl flaps control signal according to the three most important input parameters: Cylinder Head Temperature (CHT), Vertical Speed Indicator (VSI), Manifold Pressure (MP). The project uses Matlab and Fuzzy Logic Toolbox software. The authors presented the performance of the system based on twenty samples for research, which simulate position flaps. This articles presented also control surfaces, due to which it is possible to analyze controller performance. At the end showed the simulation process in the Simulink software package with the preset input values.

This paper is a continuation of research into the possibility of using fuzzy logic to assess the reliability of a selected airborne system. The research objectives include an analysis of statistical data, a reliability analysis in the classical approach, a reliability analysis in the fuzzy set theory approach, and a comparison of the obtained results. The system selected for the investigation was the aircraft gun system. In the first step, after analysing the statistical (operational) data, reliability was assessed using a classical probabilistic model in which, on the basis of the Weibull distribution fitted to the operational data, the basic reliability characteristics were determined, including the reliability function for the selected aircraft system. The second reliability analysis, in a fuzzy set theory approach, was conducted using a Mamdani Type Fuzzy Logic Controller developed in the Matlab software with the Fuzzy Logic Toolbox package. The controller was designed on the basis of expert knowledge obtained by a survey. Based on the input signals in the form of equipment operation time (number of flying hours), number of shots performed (shots), and the state of equipment corrosion (corrosion), the controller determines the reliability of air armament. The final step was to compare the results obtained from two methods: classical probabilistic model and fuzzy logic. The authors have proved that the reliability model using fuzzy logic can be used to assess the reliability of aircraft airborne systems.

The focus of this paper is to identify a method for defining the needs of logistical operational support based on the mean time to failure (MTTF) factor. The research was based on a helicopter intended for flight training. The MTTF indicator for selected equipment was determined based on failure data from previous flight operations. As the basic operational data for the developed method, the time from the beginning of the operation or the flight time from the last damage and the method of restoring airworthiness were selected. The MTTF and replacement index for the device were determined. The next step was to determine the index, based on selected probability distributions. The results were analyzed and presented in graphical form, and conclusions were drawn. Based on the MTTF index and replacement index, the logistics needs of selected devices were determined. The obtained results were compared with the actual exchanges of devices made in the year in question. The research proved that the MTTF reliability factor and the analysis of trends in value changes could be used to determine the needs for the logistical security of the operation process, particularly in relation to the equipment subject to accidental failures. This is important for maintaining high availability of an aircraft or other technical objects.

The paper presents the accuracy results of aircraft positioning using the DGLONASS method in the GBAS augmentation system in air transport. In the research test, the coordinates of Cessna 172 aircraft were recovered on the basis of the DGLONASS technique. The calculations were executed in RTKLIB software in RTKPOST library in module “DGPS/DGNSS”. The raw GLONASS data from the onboard Topcon HiperPro receiver and also from the REF1 physical reference station were utilized in the research test. In the paper, the standard deviations of aircraft coordinates and integrity HPL and VPL parameters were presented and described. In the paper, the obtained aircraft coordinates from the DGLONASS method were compared and verified with the DGPS solution. For this purpose, the RMS-3D term and difference of ellipsoidal height of aircraft were estimated in the paper. The average value of RMS-3D equals to 1.71 m, however the difference of ellipsoidal height amounts to 1.46 m, respectively.

In the era of common digitalization and far reaching progress in the field of cybernetics, it is necessary to use the knowledge and experience in military cybernetics applications. In the field of machines, control fuzzy expert inference systems open new horizons and possibilities. Generally, the main affect of human efforts in the case of artificial intelligence is to create a machine with a set of behaviors and attitudes that would allow it to work independently, with ability to adjust to changing environmental conditions and an advisory role in the decision-making process. It should be noted that this technology used in some cases has already produced successful results. This paper aims to describe how the fuzzy expert inference membership function shapes influence analysis on selected air tasks efficiency evaluation results. Presented results prove that proper fuzzy membership functions shape selection has fundamental influence on aircraft system level of efficiency evaluation (its calculation accuracy). Using this technology in military aviation air tasks efficiency evaluation aspects is pioneer. In the era of common digitalization and far reaching progress in the field of cybernetics, it is necessary to use the knowledge and experience in the domain of cybernetics in military applications. Artificial intelligence that so much influences on the imagination of scholars actually opens new horizons when it comes to control the machines. Relatively recently, it is introduced for military applications such departments of artificial intelligence as fuzzy logic, expert systems and fuzzy control theory. In this paper, fuzzy expert inference membership function shapes influence analysis on selected air tasks efficiency evaluation results are described. Presented results prove that proper fuzzy membership functions shape selection has fundamental influence on aircraft system level of efficiency evaluation (its calculation accuracy). The issue solved in the paper is based on application of theoretical results in practice. The paper can be estimated to bridge the gap between theory and practice in specific field. Using this technology in military aviation air tasks efficiency evaluation aspects is pioneer.

Purpose: Nowadays, various methods of observation from unmanned aerial vehicles (UAV) are being widely developed. There are many ways of increasing the amount of information retrieved from captured material. Unfortunately, hardware solutions consume a lot of energy, which is unacceptable in UAV applications, as it can have direct impact on the observing time on UAV. Those kinds of problems have been identified during the development phase of stabilizing platform in Polish Research Space Centre in Warsaw. As a result of that fact, energy saving control methods have been implemented, which estimates quality of stabilization process for the observation-tracking device (OTD). Design/methodology/approach: Mathematical model has been designed and validated with real-life experiments for the purpose of optimization of stabilization and control process. Two types of controlling algorithms have been implemented: linear quadratic regulator and proportional derivative method for driving the mechanism. Based on numerical simulations of the mechanical model being controlled by the mentioned driver, it was possible to define membership functions. After the process of defuzzification, the controller predicts quality of stabilization under defined environmental working conditions. Findings: An autonomous energy saving system has been created that can be implemented in many applications, where environmental conditions may change significantly. Practical implications: To test the proposed fuzzy controller, OTD has been chosen as an example object of application. It is a mechanical platform which houses the optical observation system. It is designed to provide the best working conditions during flight. Originality/value: That kind of decision-making unit has never been implemented before during observations which were carried out during flying of an object. That innovative controller should bring significant energy consumption savings.