Development of a control system for multiple unmanned aerial vehicles

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.

The paper presents the analysis on stability of digital control system for unmanned vehicle with numerical analysis. The objective of this study is mainly emphasized on the fulfillment of the advanced control techniques according to the fundamental concepts of digital control system approaches for unmanned aerial vehicle system design. The targeted unmanned aerial vehicle system was designed based on the simple construction under the idea of fixed wing flight system approaches. The stability analyses on unmanned aerial vehicle are vital role to enhance the real world applications. The background concepts on digital control system for stability analysis on dynamic control system like unmanned aerial vehicle system. The appropriate controller design for dynamic control system of unmanned aerial vehicle is vital role to analyze the accurate stability condition for reality. The implementation of numerical analysis on compensator design has been developed by using MATLAB. The physical parameters in these analyses are based on the experimental outcomes from the recent research works in dynamical system implementations. The mathematical approaches are very helpful for numerical analysis on compensator design for the unmanned aerial vehicles schemes. The simulation results confirm that the high performance stability test on unmanned aerial vehicle system has been met with the theoretical works.

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.

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.

The Flight Control System 20 (FCS20) is a compact, self-contained Guidance, Navigation, and Control system that has recently been developed to enable advanced autonomous behavior in a wide range of Unmanned Aerial Vehicles (UAVs). The FCS20 uses a floating point Digital Signal Processor (DSP) for high level serial processing, a Field Programmable Gate Array (FPGA) for low level parallel processing, and GPS and Micro Electro Mechanical Systems (MEMS) sensors. In addition to guidance, navigation, and control functions, the FCS20 is capable of supporting advanced algorithms such as automated reasoning, artificial vision, and multi-vehicle interaction. The unique contribution of this paper is that it gives a complete overview of the FCS20 GN&C system, including computing, communications, and information aspects. Computing aspects of the FCS20 include details about the design process, hardware components, and board configurations, and specifications. Communications aspects of the FCS20 include descriptions of internal and external dataflow.The information section describes the FCS20 Operating System (OS), the Support Vehicle Interface Library (SVIL) software, the navigation Extended Kalman Filter, and the neural network based adaptive controller. Finally, simulation-based results as well as actual flight test results that demonstrate the operation of the guidance, navigation, and control algorithms on a real Unmanned Aerial Vehicle (UAV) are presented.

The article discusses an approach to the formation of the basic structure of the control system for unmanned aerial vehicles, based on existing system solutions, typical specifications of the developer's boards. The characteristics of an unmanned aerial vehicle of both air and space class are given. General requirements for hardware and peripheral devices of unmanned aerial vehicles have been formed in accordance with their basic operating modes. Based on the obtained and generalized information about the developer's boards, the block-modular structure of the control system for unmanned aerial vehicles is presented. It includes all the main elements of the system and can be expanded by connecting additional boards. The advantage of this structure for debugging purposes is the presence of an FPGA on the development board.

The development of unmanned aircraft requires the development of automatic control systems for unmanned aerial vehicles. The main purpose of such control is to ensure the landing of a unmanned aerial vehicle. Landing can be considered as problem of ensuring a given glide path, which must be observed in case of vary in mass and changing unmanned aerial vehicles dynamic properties near the surface of the earth. The aim of this article is to provide analysis of perspectives in applying variable structure systems for unmanned aerial vehicles landing control with implemented sliding (quasi-sliding) motion mode where glide path is set by a function of system structure switching.

Unmanned aerial systems (UAS) with embedded machine learning applications are applied in various fields for autonomous aerial refueling (AAR), concept of parent-child UAV system, drone swarm, teaming of manned aircraft and UAV, package delivery, etc. The fundamental challenge of an air-to-air docking phase is securing between a leader and a follower aerial vehicles with effective target detection strategy. This paper proposes an autonomous docking system for unmanned aerial vehicle (UAV) system that detects, tracks, and docks to a drogue. The proposed system is operated on an onboard machine learning computer platform. This paper presents not only the design of a probe-and-drogue type of docking system based on bi-stable mechanism, but also the development of an onboard machine learning system for a simple and a robust mid-air docking. ARM-based computer, Jetson Xavier NX module, is used as a companion computer to perform a real-time detection and an autonomous control for the aerial vehicle. To employ an effective drogue detection, a deep learning convolutional neural network (CNN) based real-time object detection algorithm, YOLOv4 tiny, is applied. Furthermore, a point-cloud based tracking algorithm with a RGB-D camera system is developed to track the drogue movement in the air. Before conducting an outfield docking test, a performance of the proposed docking system is validated.

This paper discusses the issues of creating an aerial survey complex based on an unmanned aerial vehicle. The analysis of the efficiency of using aerial survey complexes based on unmanned aerial vehicles for operational monitoring of the state of natural and man-made territorial complexes is carried out. The paper considers the process of developing a modified control system for unmanned aerial vehicles, as well as the subsequent photogrammetric processing of aerial photographs. The quality of electronic units installed on unmanned aerial vehicles has been determined. The created modified control system for unmanned aerial vehicles and geographically referenced terrain orthophotomaps obtained by photogrammetric methods make it possible to classify the captured objects, perform their vectorization and provide each object with semantic information. The developed modified aerial survey complex will allow real-time monitoring of the state of natural and man-made territorial complexes based on remote sensing data from UAVs.

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.

Collective motion has been a pivotal area of research, especially due to its substantial importance in Unmanned Aerial Vehicle (UAV) systems for several purposes, including path planning, formation control, and trajectory tracking. UAVs significantly enhance coordination, flexibility, and operational efficiency in practical applications such as search-and-rescue operations, environmental monitoring, and smart city construction. Notwithstanding the progress in UAV technology, significant problems persist, especially in attaining dependable and effective coordination in intricate, dynamic, and unexpected settings. This study offers a comprehensive examination of the fundamental principles, models, and tactics employed to comprehend and regulate collective motion in UAV systems. This paper methodically analyses recent breakthroughs, exposes deficiencies in existing approaches, and emphasises case studies demonstrating the practical application of collective motion. The survey examines the substantial practical effects of collective motion on improving UAV operations, emphasizing scalability, resilience, and adaptability. This review is significant for its potential to inform future research and practical applications. It seeks to provide a systematic framework for the advancement of more resilient and scalable UAV collaboration models, aiming to tackle the ongoing challenges in the domain. The insights offered are essential for academics and practitioners aiming to enhance UAV collaboration in dynamic environments, facilitating the development of more sophisticated, flexible, and mission-resilient multi-UAV systems. This study is set to significantly advance UAV technology, having extensive ramifications for several industries.

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.

This research focuses on developing an automatic flight control system for a fixed-wing unmanned aerial vehicle (UAV) using a software-in-the-loop method in which the PID controller is implemented in National Instruments LabVIEW software and the flight dynamics of the fixed-wing UAV are simulated using the X-Plane flight simulator. The fixed-wing UAV model is created using the Plane Maker software and is based on existing geometry and propulsion data from the literature. Gain tuning for the PID controller is accomplished using the pole placement technique. In this approach, the controller gain can be calculated using the dynamic parameters in the transfer function model and the desired characteristic equation. The proposed controller designs' performance is validated using attitude, altitude, and velocity hold simulations. The results demonstrate that the technique can be an effective tool for researchers to validate their UAV control algorithms by utilising the realistic UAV or manned aircraft models available in the X-Plane flight simulator.

This paper presents the design and development of the LinkBoard, an advanced flight control system for micro Unmanned Aerial Vehicles (UAVs). Both hardware and software architectures are presented. The LinkBoard includes four processing units and a full inertial measurement unit. In the basic configuration, the software architecture includes a fully configurable set of control modes and sensor fusion algorithms for autonomous UAV operation. The system proposed allows for easy integration with new platforms, additional external sensors and a flexibility to trade off computational power, weight and power consumption. Due to the available onboard computational power, it has been used for computationally demanding applications such as the implementation of an autonomous indoor vision-based navigation system with all computations performed onboard. The autopilot has been manufactured and deployed on multiple UAVs. Examples of UAV systems built with the LinkBoard and their applications are presented, as well as an in-flight experimental performance evaluation of a newly developed attitude estimation filter.