IMPLEMENTATION OF COMPLEX SOLUTIONS FOR PROTECTION AGAINST CYBER THREATS OF ELECTRONIC SYSTEMS OF UNMANNED AERIAL VEHICLES

The classification of drones - both military and civilian according to the relevant criteria - is presented. Block diagrams of a typical unmanned aerial vehicle and its power system are shown. Typically, a drone power system of the "micro", "mini" or "short range" category, according to the UVS international classification, is a set of DC / DC converters with a microprocessor control system. The power source for such aircraft is usually a battery, less often - fuel cells. During the flight, the engine speed is variable, and its change depends not only on changes in flight speed or direction, but also on weather conditions, such as wind, as the stabilization system constantly aligns the drone. This leads to the fact that the power supply system of such a device is actually a significant part of the time in transition condition. This leads to a significant content of the component of exchange energy that battery consumed which in turn will increase losses, and thus reduces the range of the unmanned aerial vehicle. The phenomenon of the occurrence of exchange power in the power supply systems of electric vehicles which powered from DC sources and specifically in the power supply system of an unmanned aerial vehicle is analyzed. The time diagrams of current, voltage, active and inactive components of power consumed from the mains power supply network of electric locomotive DE1 are illustrated. It can be seen that with a sharp change in the modes of operation of traction units there is a significant component of exchange power in the motor-network system. Such processes are typical for almost any electric vehicle and are associated with the presence of a significant number of reactive elements in the power supply systems, as well as frequent changes in load parameters. A block diagram of a typical unmanned aerial vehicle is presented. The unmanned aerial vehicle system consists of three parts: the air part, the unmanned aerial vehicle itself, the ground control station, which can be autonomous or manned, the control system, which provides communication and data transmission. The block diagram of the power system of a typical unmanned aerial vehicle is presented A simplified schematic diagram of the DC motor power supply system is presented. The relations for determining the amount of exchange power in the power supply system of an unmanned aerial vehicle are derived. It is concluded that to reduce the impact of this phenomenon, it is necessary to modify the power supply system by adding compensation units of inactive power component.

Solo operation of multi-unmanned Aerial Vehicle (UAV) will be the trend of future, and operators play a significant role in the UAV supervisory control system, but human may be impacted by all kinds of factors, which may decline the performance of UAV system. In this paper, modeling is conducted for the behavioral characteristics of operators in the multi-UAV supervisory control system with improved Hidden semi-Markov Model (HSMM), and the relationship between the predication result and anomaly of HSMM model is analyzed. This method can be applied for monitoring the anomaly in the behaviors of operators, which is of strong and practical significance in the multi-UAV supervisor control system and Human Supervisory Control (HSC) system. The current Unmanned Aerial Vehicle (UAV) system still adopts the manipulation of UAV by several operators. In order to realize the manipulation of multi-UAV by single operator, a lot of studies have been conducted in the automation of multi-UAV control and man-machine work allocation, etc. (1); with the improvement of automation of UAV system, the operation of multi- UAV by single operator will be favourable in the future, and it will also become a significant part in the future network centric warfare (2). There are many differences in the control of UAV by single operator and current UAV control system. In the traditional UAV system, operators mainly control the UAV manually, while in multi- UAV control system, the automatic system takes charges of the majority of operation, and the operators are mainly responsible for the supervision and control of UAV system, as well as the intervention and decision in emergencies beyond the handling of automatic system. Consequently, the future multi-UAV system is a typical Human Supervisory Control (HSC) system (3). In this paper, modeling is conducted for the behaviors of operators in the UAV HSC system with Hidden semi-Markov Model (HSMM) with the experimental data as the drive. When there are anomalies in the behavioral characteristics of operators, the relationship between the prediction result and abnormal behavior of HSMM model is analyzed. With this method, the real-time supervision and analysis of the behavioral characteristic anomaly is implemented in the UAV supervision and control or other HSC scenes.

Currently, such expert systems that are used in the “pilot advisor” mode are widely used in manned aircraft. The main task that these systems allow to solve is that it becomes possible to formulate recommendations when the pilot has an acute lack of time to make appropriate decisions. Manned aircraft are being replaced by unmanned aerial vehicles, which entails changes in the intelligent navigation and control system of such aircraft. The main feature of the corresponding intelligent navigation and control system is the objective need for the formation and implementation of solutions with minimal involvement of personnel of the corresponding unmanned aerial system. The article discusses the structure and model of an on-board expert control system for a promising unmanned aerial vehicle. The structure of the interaction of the proposed promising on-board expert control system for an unmanned aerial vehicle with sources of initial data and consumers of the formed control solutions is presented. The main issues of the organization’s work on the formation of the goals of the on-board expert management system are considered. The main issues of operation of an on-board expert control system of a promising unmanned aerial vehicle are considered.

Relevance Today, there is a growing demand for the unmanned aerial vehicles usage to solve various types of problems. Moreover, unmanned aerial vehicles often designed and manufactured using standard imported components. The creation of electric unmanned aerial vehicles is promising, due to their environmental friendliness and reliability. Such aircraft are based on electric propulsion systems — electrotechnical complexes and systems consisting of an electric motor, an inverter electronic unit and a propeller. Aircraft type electric unmanned aerial vehicles are widespread due to their high range and flight time. Electric motors of aircraft type unmanned aerial vehicles are subject to increased requirements for noise and vibration levels, since the body of aircraft-type unmanned aerial vehicles can act as a resonator. As part of programs to ensure import independence of the Russian Federation, the development and research of electric motors for propulsion systems of electric unmanned aerial vehicles, including aircraft types, are relevant. Aims of research The main aim of the research is to determine the current technical and scientific level of developments in the field of electric motors for unmanned aerial vehicles. Identification of features and trends in research and development in the field of electric motors for unmanned aerial vehicles. Design, manufacture of experimental samples and research a brushless permanent magnet electric motor for unmanned aerial vehicles. Identifying a series of works aimed at developing a methodology for the design and research of electric motors for propulsion systems of unmanned aerial vehicles. Research methods During the design, methods of analytical calculation and computer finite element modeling were used. Experimental research methods were used to validate computer models and determine whether the created electric motor met the required parameters. To conduct experimental studies, a special stand was used with the ability to measure the thrust of the propulsion system. In the future, it is planned to use 3D scanning methods and restore the geometry of propellers for coupled models. Results As a result of the work carried out, an electric motor for aircraft-type unmanned aerial vehicles was developed and researched. Features that must be considered during design were identified. Several works have been identified that will be carried out as part of the design and research of electric motors for unmanned aerial vehicles, aimed at creating a new high-precision interdisciplinary design methodology. The work carried out is the basis for the development of new and scientific approaches to the creation of electric propulsion systems for unmanned aerial vehicles.

In todays world, the applications of Unmanned Aerial Vehicle (UAV) systems are leaping by extending their scope from military applications on to commercial and medical sectors as well. Owing to this commercialization, the necessity to append external hardware with UAV systems becomes inevitable. This external hardware could aid in enabling wireless data transfer between the UAV system and remote Wireless Sensor Networks (WSN) using low powered architecture like Thread, BLE (Bluetooth Low Energy). The data is being transmitted from the flight controller to the ground control station using MAVLink (Micro Air Vehicle Link) protocol. The ideal aim of this research is to address the issues of integrating different hardware with the flight controller of the UAV system using a light-weight protocol called UAVCAN. This approach would result in reduced wiring and would harness the problem of integrating multiple systems to UAV.

Autonomous collision avoidance system (ACAS) for Unmanned Aerial Vehicles (UAVs) is set as a tool to prove that they can achieve the equivalent level of safety, required in context of integrating UAVs flight into the National Airspace System (NAS). This paper focus on the cooperative avoidance part, aiming to define an algorithm that can provide avoidance between cooperative UAVs in general, while still be restricted by some common rules. The algorithm is named the Selective Velocity Obstacle (SVO) method, which is an extension of the Velocity Obstacle method. The algorithm gives guidelines for UAVs to select between three basic modes for avoidance, i.e., to Avoid, Maintain, or Restore. The variation of those three modes gives flexibility for UAVs to choose how will they avoid. By modeling the algorithm as a hybrid system, simulations on various UAVs encounters scenario were conducted and shows satisfying result. Monte Carlo simulations are then conducted to conclude the performance even more. Randomizing the initial parameters, including speed, attitude, positions and avoidance starting point, more than 10 encounter scenario were tested, involving up until five UAVs. A parameter called the Violation Probability is then derived, showing zero violations in the entire encounter samples.

The article describes the results of the experimental study on the influence of operator’s activities on the control system of a heterogeneous unmanned aerial vehicles’ group. The proposed mathematical apparatus allows to present the actions of the operator as part of the automated control system, to carry out a quantitative assessment of the efficiency of the operator’s actions. It also allows to evaluate the impact of the results of this activity on the effectiveness of solving tasks in the control system of an unmanned aerial vehicles’ group. The given experimental data and obtained laws of distribution of various random variables can be used in modelling the activity of the operator in complex control systems of an unmanned aerial vehicles’ group. Management of operators’ activity models enables to improve the quality of the development of decision support system.

This paper proposes the design and development of an on-board autonomous visual tracking system (AVTS) for unmanned aerial vehicles (UAV). A prototype of the proposed system has been implemented in MATLAB/ Simulink for simulation purposes. The proposed system contains GPS/INS sensors, a gimbaled camera, a multi-level autonomous visual tracking algorithm, a ground stationary target (GST) or ground moving target (GMT) state estimator, a camera control algorithm, a UAV guidance algorithm, and an autopilot. The on-board multi-level autonomous visual tracking algorithm acquires the video frames from the on-board camera and calculates the GMT pixel position in the video frame. The on-board GMT state estimator receives the GMT pixel position from the multi-level autonomous visual tracking algorithm and estimates the current position and velocity of the GMT with respect to the UAV. The on-board non-linear UAV guidance law computes the UAV heading velocity rates and sends them to the autopilot to steer the UAV in the desired path. The on-board camera control law computes the control command and sends it to the camera's gimbal controller to keep the GMT in the camera's field of view. The UAV guidance law and camera control law have been integrated for continuous tracking of the GMT. The on-board autopilot is used for controlling the UAV trajectory. The simulation of the proposed system was tested with a flight simulator and the UAV's reaction to the GMT was observed. The simulated results prove that the proposed system tracks a GST or GMT effectively.

System for unmanned aerial vehicles (UAV) advanced alternative energy (SAvE) is a research project funded in 2007 by Piemonte Regional Government, Italy, and assigned to Politecnico di Torino and Alenia Aeronautica. Aim of the project is the study of new, more efficient, more effective, and more environmentally friendly on board systems for future advanced UAV, particularly for future advanced medium altitude long endurance (MALE) UAVs. This article deals with the analysis and design of the all electric secondary power system of a future advanced MALE UAV that is considered as ‘reference aircraft’. After a thorough trade-off analysis of different configurations of the secondary power system, the hybrid fuel cells configuration, characterized by starter/generators, fuel cells, and traditional and innovative batteries, has been selected as the most promising. Detailed investigations to find the best way to apportion the supply of secondary power, considering the various power sources (starter/generators, batteries, and fuel cells) in the different modes of operations, have been performed thanks to an integrated simulation environment, where physical, functional, and mission scenario simulations continuously exchange data and results.

In this study, a robust <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> networked security observer-based reference tracking control scheme is proposed for the stochastic quadrotor unmanned aerial vehicle (UAV) system under malicious attacks on the actuator and sensor of network control system (NCS). To reduce the computational burden on UAV system, the UAV system is connected with a remote computing unit and the complicated tracking control command can be calculated by remote computing unit. By using the novel discrete smoothed model, the model of attack signals on actuator and sensor can be embedded in system state of UAV and thus the attack signals as well as the quadrotor system state can be simultaneously estimated through a conventional Luenberger observer. Further, the corruption of attack signals on state estimation of UAV is also avoided. To eliminate the effect of unavailable external disturbance and intrinsic fluctuation during the reference tracking control process, a robust <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> networked security observer-based reference tracking control scheme is introduced to attenuate their effects on the NCS of quadrotor UAV. By using the characteristic of convex Lyapunov function, the design condition of robust <inline-formula> <tex-math notation="LaTeX">$H_{\infty }$ </tex-math></inline-formula> networked security observer-based tracking control is derived in terms of the nonlinear functional inequalities. Since the nonlinear functional inequalities are not easy to be solved analytically or numerically, the Takagi-Sugeno (T-S) fuzzy interpolation technique is employed to interpolate the nonlinear stochastic quadrotor NCS by a set of linear local systems via fuzzy bases. In this case, the nonlinear functional inequalities can be converted to a set of linear matrix inequalities (LMIs) which can be easily solved by the MATLAB LMI TOOLBOX. Simulation results are provided to validate the effectiveness of the proposed method in comparison with conventional robust observer-based T-S fuzzy tracking control scheme.

The purpose of this work is the analysis of the power supply system of unmanned aerial vehicle. One of the most important tasks of this system is to ensure the smallest possible losses in order to achieve greater endurance of the aircraft, which means – the ability to complete the mission. The presence of an inactive component of consumed power obviously reduces the efficiency of the entire unmanned aerial vehicle. Considering also that due to the influence of wind, speed changes and other factors, the power system spends a significant amount of time in the transition mode, the impact of this phenomenon becomes even more significant. Thus, the phenomenon of the occurrence of exchange power in the power supply system of an unmanned aerial vehicle is analyzed. One of the most common solutions for unmanned aerial vehicles is the use of a BLDC motor, which is a further development of DC motors and was created with the aim of improving their basic characteristics. This type of engine has gained its popularity due to numerous advantages: high reliability, efficiency, speed and others. The principles of control of the BLDС engine are given. The unmanned aerial vehicle power supply system, built on the basis of a buck converter and a bridge inverter, was analyzed. An equivalent circuit of the converter is built, taking into account the losses in the electric circuit. On its basis the relations for determining the value of exchange power in the power supply system are derived. With the help of these expressions, it is possible to determine the value of the exchange energy at an arbitrary time interval in the real power supply system of the aircraft. A model of the power supply system of an unmanned aerial vehicle with a BLDC engine was built in the Matlab Simulink software environment. A time diagram is obtained, on the basis of which it is possible to draw a conclusion about the content of exchange power in the converter circuit. To minimize this phenomenon, it is necessary to develop a compensation system or an intelligent control system.

Abstract. The collection and updating of 3D data is the one of the important steps for GIS applications which require fast and efficient data collection methods. The photogrammetry has been used for many years as a data collection method for GIS application in larger areas. The Unmanned Aerial Vehicles (UAV) Systems gained increasing attraction in geosciences for cost effective data capture and updating at high spatial and temporal resolution during the last years. These autonomously flying UAV systems are usually equipped with different sensors such as GPS receiver, microcomputers, gyroscopes and miniaturized sensor systems for navigation, positioning, and mapping purposes. The UAV systems can be used for data collection for digital elevation model DEM and orthoimages generation in GIS application at small areas. In this study, data collection and processing by light UAV system will be evaluated for GIS data capture and updating for small areas where not feasible for traditional photogrammetry. The main aim of this study is to design the low cost light UAV system for GIS data capture and update. The investigation was based on the aerial images which recorded during the flights performed with UAV system over the test site in Davutpasa Campus of Yildiz Technical University, Istanbul. The quality of generated DEM and ortho-images from UAV flights was discussed for GIS data capture and updating for small areas.

On parallel hybrid-electric propulsion system for unmanned aerial vehicles

The expediency of using a compensation radiometer (CR) with periodic absolute calibration as a sensor for preprocessing the information of correlation-extreme navigation systems (CENS) of unmanned aerial vehicles (UAV) was shown. This is determined by the possibility of obtaining and using the estimates of gain fluctuations obtained in previous frames which will provide an increase in the radiometer sensitivity. In addition, due to the accumulation of information, an increase in accuracy of measurement of the elements of the current image formed by the CENS will be provided. The algorithm of processing the obtained calibration estimates during linear processing corresponds to a certain digital filter (DF). By defining a set of the DF weight coefficients, it is possible to improve the CR fluctuation sensitivity by reducing the gain fluctuations. Up to 1.8-time gain in sensitivity can be reached for typical frequency and time parameters of the compensation radiometer of UAV CENS. The problem of synthesis of a digital filter was set. A solution to the problem of synthesizing an optimal digital filter was proposed. Its use in a CR will improve the fluctuation sensitivity. In its turn, this will make it possible to improve the quality of a current image generated by the system when siting by means of sighting surfaces with low-contrast objects taking into account fluctuations in radio-brightness temperature. It was found that the gain in sensitivity when using the optimal digital filter increases with an increase in the operating period of the radiometer and an increase in the digital filter order. Improvement of fluctuation sensitivity of the CENS data preprocessing system is important for UAV location in low-contrast areas

The objective of this paper is to design an autopilot system for unmanned aerial vehicle (UAV) to control the speed and altitude using electronic throttle control system (ETCS) and elevator, respectively. A DC servo motor is used for designing of ETCS to control the throttle position for appropriate amount of air mass flow. Artificial Intelligence (AI)-based controllers such as fuzzy logic PD, fuzzy logic PD + I, self-tuning fuzzy logic PID (STF-PID) controller and fuzzy logic-based sliding mode adaptive controller (FLSMAC) are designed for stable autopilot system and are compared with conventional PI controller. The target of throttle, speed and altitude controls are to achieve a wide range of air speed, improved energy efficiency and fuel economy with reduced pollutant emission. The energy efficiency using specific energy rate per velocity of UAV is also presented in this paper.