1
Survey: A context of Unnamed Aerial Vehicle of
Multi-rotors type
Abstract—The article presents a survey of what has been studied in the area of Unnamed Aerial Vehicle. It conducted an analysis of what has already been published in the area in order to raise what are the main approaches for UAV. The main topics covered in this work were: control UAV, physical modelling, drones swarm and finally the comparison between the topologies of UAV. The results of this work is a discussion of what was found in each of these topics, as well as propose future work related to these areas of research. The contribution is to offer more information for researches about the situation of the main areas of UAVs, also show different approaches available in the bibliography.
I. INTRODUCTION
The robots have been replaced the human labor for continu-ous work and high level of complexity and dangercontinu-ous work, for example bombs disposal. Among the is possible emphasize the Unnamed Aerial Vehicles (UAVs). It is possible find different kinds of UAVs such as with one or more motors, also with distinct architectures (varying from two motors till six motors). According to [1], these vehicles basically is a type of aircraft that do not realize an pilot to drive, the basis of them are computational and an analysis of aircraft dynamic forces.
According to [2] , for some time it was common to associate this type of aerial vehicle to military applications, it has been happening since 50, but with the advancement of technology it has become popular in the civil applications. It is remarkable the growing use of UAVs for different applications, such as the recognition of areas that may or may not present a risk to human life, the surveillance of dams, plantations and border regions.
The drones can be found in different forms, in the context of this work, there will be a survey of the following topologies: tricopter, quadcopter and hexacopter.
A quadcoper, also know as quadrotor, is a helicopter with four propellers. The motors are directed to upward and with the square formation with equal distance from the center of mass. The quadcopter is controlled by adjusting the angular speeds of each propeller that are rotated by electric motors. This topology is a typical project for small UAVs, because the structure is simple. It is possible to find this architecture in two types: Plus and X. [3]
The hexacopter is considered an aerial vehicle with six propellers and located at the vertices of a hexagon and the same distance from the center of mass. The propulsion system consists of three pairs of counter-rotating fixed pitch propeller. Their control is similar to the quadcopter.
In this survey will be present a systematic review and discussion about which has been researched in the topologies described in the last paragraph. The topics that will be focus are: control systems, network router, comparative between
topologies and different approaches in mathematical model. The main objective is find which area needs more attention for future work, in otherwise show the UAV research areas with consistent results in different approaches.
II. UNNAMED AERIALVEHICLES
The UAVs research starts during the century 19, with the use of balloons with bombs to attack enemy city in Austrian attacks against the city of Venice. The use of unmanned aerial vehicles grew even more in 1¨ı¿12 World War [4], Figure 1 shows one of the models of UAV used in war. From then until the present day, research involving UAVs have not stopped, now can be found different types of UAVs for different applications, these studies are directed to the control, design, endurance and speed.
Fig. 1. UAV model used in 1¨ı¿12 World War
Nowadays it is possible to find UAV multirotors in different applications, such as: industry , mining, agriculture, civil construction and exploration of environment.
According [5], a simple point of view of what a UAV is, an aircraft where the pilot is substituted by a computer system. It is known that it is much more complex than that, but it is much more complex than just that. An aerial vehicle needs its own design for a particular application.
In [6], the design of a UAV, should follow the following characteristics:
• Possess controllability enough to stay in level flight and to get out of a state of equilibrium to another security;
• Control forces must be within the allowable limits set in the project, taking into account the entire flight envelope;
• The aircraft to be able to remain stable throughout the
flight route.
It is possible to find UAVs multirotors in different topolo-gies such as: tricopter, quadcopter, pentacopter, hexacopter and octacopter. In the follow subsections will be present an introductory information about each topology.
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A. Tricopter
The tricopter is a variation of the helicopter, having three rotors each of its ends. can be found in two different formats, they are:
• Structure in the shape of a ’Y’ - Where the two front
engines make the heading and the rear engine is in charge of the direction. Figure 2 presents a model of UAV in this architecture;
• Structure in a ’T’ shape - Its operation is similar to ’Y’, but has the differential related to the rear arm, which can perform such rotation around its own axis, allowing a greater variety of movements.
Currently you can not find many ongoing research with this topology, because it does not have significant advantages when compared to the hexacopter or quadcopter. The differential of this topology over the other are low cost and easy assembly.
Fig. 2. Tricopter Structure
B. Quadcopter
The first quadcopters (and multirotors) emerged in 1904, where in an attempt to make a small autonomous helicopter was carried out by Charles Richet. Years later, the brothers Jacques and Louis Br¨ı¿12guet, developed the Gyroplane I.
According to [7], the development of quadricopters not had much evolution after 1956 due to its low efficiency, only recently returned to the subject of research and development due to technological change to meet the needs that once made them unviable as materials lightweight, fast controls and high efficiency sensors. Unlike the early quadricopters, its current purpose is not to carry passengers with a cabin in its structure. In the paper [8] , the project consisted of a structure where each end containing a rotor, where each pair was placed to rotate in one direction, nullifying the structure torque reaction, The Figure 3 show an example of the structure of a quadcopter. In 1922, the Russian Georges Bothezate, working for the US Army, created the Flying Octopus, one quadcopter with 1678 kg powered by a 220 HP engine.
Fig. 3. Quadcopter Structure
Basically, a quadcopter consists of a UAV with four ends, each having a motor and a propeller, it can be found in two forms, namely: the letter ’X’ and Plus. The formats not directly influence the design model, but the UAV behavior. This topology offers some advantages, they are:
• Low cost manufacturing;
• Good maneuverability;
• Enough power item to add accessories;
• Great traction and power when compared to tricopter. C. Hexacopter
The hexacopter is the next step of a quadrotor. These models has six corresponding engines and propellers. This contributes to the capacity of the aircraft and really makes the ideal choice for anyone flying with expensive cameras attached. Figure ?? presents the hexacopter architecture. Essentially, these models have all the advantages of quadcopter, but has some advantages such which are:
• Power: These models have higher speeds and more power
because of the two extra engines included;
• Height: A Hexacopter reaches higher altitudes easily
compared to its counterpart;
• Security: Why have 6 engines 120 degrees away, a motor can go into a fault condition, the UAV will not fall. This means that a driver will be able to land safely even if an engine is damaged.
III. RESEARCHMETHOD
In this phase, the major objective is identify the reasons of produce an SLR and define a protocol how to conduct it. Basically, in this phase the research questions are defined making clear reasons of the produce this survey.
A. Questions
The goal is identify what are the subjects in UAV have been researched, and a breath analysis of the results. To achieve this answers, some questions were defined?
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Fig. 4. Quadcopter Structure
• RQ2 - Is the results founded were satisfactory?
• RQ3 - What are the methods used for solve the problems?
• RQ4 - What are the challenges to be solved? B. Review Protocol
The review protocol is used to execute de survey. With the review is possible reduce and define the scop of this research. Basically the review protocol is a description of all procedure of search, describing all the elements of the search state such as source selection, description of the studies process and extraction strategies. The search process was conducted manually in May 2015, without a specific journal or conference. Basically for research, keywords were used, started for the main topic, in this case UAV, and splitting in the subtopics bases on the results founded in the main topic.
The procedure of source selection was made following the main databases in computer engineering, these databases contains journals and conference papers in topics relation to robotics, including UAV. The sources used was: Scielo, IEE Xplorer, Capes Periodic, ACM Digital Library, Google Scholar and Springer.
The string key words used were:
• UAV
• Control Systems for UAV • Topologies of UAV • Drones
• Drones Swarm C. Quality Assessment
For the quality assessment of the research was evaluated using the method used by New York University, with the search criteria bi the Center for Review and Dissemination Database of Abstracts of Review Effects criteria (Ref). This criteria is based in four questions
1) Are the reviews inclusions and exclusions criteria de-scribed and appropriate?
TABLE I
QUALITYASSESSMENTSTUDIESSCORE. Paper QA1 QA2 QA3 QA4 Score
[9] Y Y Y Y 4 [10] Y Y Y Y 4 [11] Y P P Y 3 [12] Y Y P Y 3.5 [13] Y Y Y Y 4 [14] Y Y Y Y 4 [15] Y Y N Y 3 [16] Y Y Y Y 4 [17] Y Y Y Y 4 [18] Y Y Y Y 4 [19] Y Y Y Y 4 [20] Y Y Y Y 4 [21] Y Y Y Y 4 [22] P Y Y Y 3.5 [23] Y Y Y Y 4
2) Is the literature search likely to have covered all relevant topics of UAV?
3) Did the review assess the quality/relevant results? 4) Where the basic data/studies adequately described? The answers for each question were divided to satisfy each topic that this study was divided. The questions were scored as follows:
• QA1 - Y(yes), all the criteria are clear in the paper, P (Partly), the inclusion of the criteria is not so clear in the paper, N(no), the inclusion criteria are not defined and cannot be readily inferred.
• QA2 - Y, the authors have either searched 3 or more papers relationed with the subject, P if just 2 papers, and N if the paper has just 1.
• QA3 - Y, the authors have explicity defined a methodol-ogy to develop the work and if the results are satisfatory, P in case of the research question involves quality issues that are relationed with the study. N in case of the quality and the goals of the paper are not satisfatory relationes of the main topic.
• QA4 - Y information is present about each study, P only
symmary information about primary studies is presented, N the results of the individual primary studies are not specific.
The scoring procedure was Y = 1, P = 0.5, N = 0, or Unknown (i.e. the information is not specified). Kitchenham coordinated the quality evaluation extraction process. Kitchen-ham assessed every paper, and allocated 4 papers to each of the other authors of this study to assess independently. When there was a disagreement, we discussed the issues until we reached agreement. When a question was scored as unknown we e-mailed the authors of the paper and asked them to provide the relevant information and the question re-scored appropriately. D. Data Collection
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• The source (journal or conference) and full reference.
• Classification of the study Type (SLR, Meta-Analysis
MA);
• Scope (Research trends or specific technology evaluation
question).
• Main topic area.
• Summary of the study including the main research ques-tions and the answers.
• Research question/issue.
• Quality evaluation.
How many primary studies were used in the SLR. One researcher extracted the data and another checked the extrac-tion. The procedure of having one extractor and one checker is not consistent with the medical standards summarized in Kitchenham guidelines (Ref), but is a procedure we had found useful in practice. Kitchenham coordinated the data extraction and checking tasks, which involved all of the authors of this paper. Allocation was not randomized, it was based on the time availability of the individual researchers. When there was a disagreement, we discussed the issues until we reached agreement.
IV. SYSTEMATICREVIEW
In this section will be present the results of the systematic review, where is divided into four main topics, these topics was divided in:
• Mathematical Modeling
• Control Systems for UAV
• Drones Swarm
• Comparative between different types of UAV A. Mathematical Modelling
Mathematical modeling of UAVs is to present mathematical formulas that represent the movements and the forces acting on it, for example, torque, thrust and drag. You can also represent from these models displacement, rotational movement and an-gular velocities. The physical model is the first step to conduct a study of the behavior of UAVs, as well as establishing a control system. Following are different approaches to models found for UAVs multirotores, most of these approaches are in jobs that also involve the control system design, which will be discussed in the next subsection.
The mathematical models of the UAV are strong relation with the physical laws, in special for calculate the speed and the dislocation. In the [9], showed the model for a quadcopter. In this work, there are important definitions such as the coordinate systems evolved with the UAV. Also, the model of the resultant forces base in Newton-Euler method that consider the forces in each axis that acts in the system. The advantage of this model is that easy adaptable for all topologies of UAV multi-rotors, also, as it is the result of forces, just add the forces that each rotor impact on the system as a whole.
Another approach, the paper [12] showed the mathematical model of a mini rotorcraft with six rotors. The equations was defined by means of quaternion because, unlike Euler angles, they do not suffer from the gimbal lock; they are also more efficient in terms of numerical computation and, in addition,
any operations involving them is trivial. This model shows the resultant forces to keep the aircraft on the air, such as he trust. This model is different when compare with the others, the main difference is exactly the use of the quaternions to represent rotation of a rigid body instead of the Euler Angles. In the [13], a mathematical modelling of UAV or hexacopter based on Port-Controlled Hamiltonian (PCH) systems and a basic modelling using Newton Euler model were presented. This model then can be used to develop proper method for stabilization and trajectory control of the hexacopter system. The model is based on the total energy in the system and is separated into subsystem which utilized the exist intercon-nections. The main advantages of this PCH approach due to preservation of the non linearity of the model by using port-controlled Hamiltonian system and the energy balance in the system can be attained by shaping the internal energy while stabilizing the system. By using the PCH approach, the links between energy storage elements, dissipative (resistive) elements, and the environment is emerged when modelling a physical system. The first part of this approach uses Newton-Euler method, after the PCH method is used, different from the others approaches presented in other works.
When compared, the approaches, it is preferable to work with the first based on a result of forces and Newton-Euler model. This is because this model is easy to understand be-cause it is based on the physical equations of motion and does not have work to perform parametrization for representing characteristics of a particular topology.
B. Control Systems for UAV
There are many jobs related to UAVs control multirotores type, varying depending on the application, the main ap-proaches found are related to control altitude and stability of UAVs. The main controls that have been implemented in different works were the Proportional Integral Derivative and (PID) and the fuzzy controller, however, other drivers not so used have also been implemented, as well as intelligent algorithms.
In work [14], a control method for synthesis has been proposed to control the attitude and the position of a Quad-copter based on a dynamic model of the engine on which this model is underactuated, nonlinear and highly coupled. The dynamic model is divided into subsystems, each subsystem in which this controller will act to ensure that the state variables convergam to the desired values. Finally, to demonstrate the robustness of the proposed control method, the author takes into consideration the forces and aerodynamic moments and air drag taken as external disturbances are taken into account, the obtained simulation results show that the control method synthesis performs well in terms of position and attitude tracking when faced with external disturbances. In this work the moment of inertia caused by drivers is considered low, and the factor is ignored, this may invalidate the results obtained when this control system is subjected in a real environment, not simulation.
In [15], [22] proposes a fuzzy controller and a PID con-troller for a quadcopter, both applied to the same system
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in order to compare the performance of both to determine which is best. Both controllers have as the goal of realizing the take off and landing of the vehicle, without considering other movements. The PID is a process control technique which links the derivative actions, integral and proportional, thereby causing the error signal is minimized by the pro-portional action, integral action and zeroed by obtained with a preemptive rate by derivative action. In additional, Fuzzy controllers allows quantification possibilities. Comparing it to boolean logic, with fuzzy logic is able to quantify how much something is false or is true, the fuzzy sets in this work was precisely the attitude of the UAV. Regarding the comparison of the two controllers, for the experiments of this study, the fuzzy controller showed a faster stability. Note that it is only two movements analyzed (takeoff and landing), you can not say which of the drivers would be better based on these results for a flight route. Other controllers using Fuzzy Logic is present in [23], where was used a combination of Fuzzy Logic Control and Model Reference Adaptive Control will be developed to stabilize and control a fixed-wing UAV.
In the work [16], [10], [11] similar to [15] a PID con-trol is proposed, with the difference that this work involves controlling the trajectory control. The PID in this case was based on quaternion for hexacopter control and stabilization. The quaternion parametrization is applied instead of Euler angles for describing the orientation drone because Latter These might induce the lost of a degree of freedom in the dynamic system if the gimbal lock configuration is reached. At work two experiments were tested for different trajectories, the parameter quaternion in conjunction with the PID showed results as desired the planned trajectory. The advantage of this approach consists precisely in uniting two techniques in favor of seeking a better system stability. You can also find path contorls using Fuzzy, such as in the work [18]. Fuzzy controller is proposed to hexacopter position, where the fuzzy rules are developed using expert knowledge, if the pilot.
Another approach used in the [17], a controller for recov-ery (landing) was design of a small fixed-wing UAV on a frigate ship deck. The control laws are encoded in a way common for Genetic Programming. However, parameters are optimized independently using effective Evaluation Strategies, while structural changes occur at a slower rate. The fitness evaluation is made via test runs on a comprehensive 6 degree-of-freedom non-linear UAV model. The results show that an effective controller can be designed with little knowledge of the aircraft dynamics using appropriate evolutionary tech-niques. The results is not better than PID and Fuzzy control, because evolutionary techniques requires more time to achieve the stability, and in real time the situation is worse because the situation are in constant changes.
C. Drones Swarm
Swarm intelligence has received much research attention in recent years. Swarm intelligent systems generally exhibit de-centralized control achieved through simple agent behaviours and interactions developing a self-organization that is con-sidered an emergence of order from the system. In UAVs
TABLE II
COMPARATION BETWEENUAVTOPOLOGIES.
No. Type of copters No. of rotors Stability Lifiting Power 1 Bicopter 2 Less stable Very low 2 Tricopter 3 Less stable Very low 3 Quadcopter 4 Stable Average 4 Pentacopter 5 Less stable High 5 Hexacopter 6 High stable High 6 Octacoper 8 Most stable Very high
it consist in coverage a determinate area with a number of UAV, where each UAV represents a capacity of cover and the objective is cover all region specified. One of the most common application is use drones swarms for distribute signal of internet for a specific area such as stadiums.
In [19] an agent-based simulation for dynamic coopera-tive cleaning is augmented with additional behaviours and implemented into a Dynamic Data-Driven Application Sys-tem (DDDAS) framework for dynamic swarm control. Dy-namic Data Driven Application Systems (DDDAS) describes a paradigm where a system incorporates simulated data into the real-time decision process while retaining the ability to dynamically manage sensors to refine measurements. The result of this work is use DDDAS in a drone swarms for achieve all the points of a map.
The paper [20] presents findings from a meta-analysis of 27 UAV swarm management. This swarm is managed by the human-system interface and human factors concerns, provid-ing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. The challenge in this work was show how the human guidance can improve the perform of a UAV swarm for specific missions. Also, this work show limitations because it is just a simulation, and the behaviour of the drones could change in the real situations, and when the swarm is control by a human is hard to predict unexpected situations.
D. Comparative between different types of UAVs
One of the biggest challenges in the drone project is set topology which is best for a particular application. For every application type, new requirements can be established, for example, speed, manoeuvrability, weight, among others. To meet these requirements, different types of topologies should be analysed to complete what each can offer to meet the requirements of my application. There a number of satisfactory works comparing the different types of UAV was found, the main work to be discussed is [21] . The author makes a superficial comparison the following topologies UAVs multi-rotors. • Bicopters; • Quadcopters; • Pentacopters; • Hexacopters; • Octacopers.
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The comparison made by the author was with analytical basis without performing simulations. The results presented in Table II, showing a surface comparison in the number of rotors, stability and energy expenditure. To compare the energy expenditure the author took into account only the number of rotors used by each topology, where as a result, the topology with larger rotors will have a greater energy expenditure.
Regarding stability, the author took into account the fact that the topology of each format. It was concluded that more symmetrical architectures will provide better stability, espe-cially with loads paths, which is necessary for the UAV can withstand the potential instability caused by external forces such as wind.
In more detailed search topologies comparison was not possible to find out more detailed studies, which involve sim-ulations, performance comparison, or even different headings for the same topology. For UAV is extremely important to have an indication of what topology is best for each application, unfortunately there are few results to show an efficient and clear comparison of different types of UAVs.
V. RESULTS
In this section, the research questions are answered, using the data collected in the studies.
A. RQ1 - What are the main topics in UAV area?
The UAV research is still recent, it was possible to filter the goals based in the keywords and the results, according to the level of the interest of the topic and the contribution.
The most works founded in the bibliography was talking about the control systems, there are a lot of works involving this, using different techniques to control the UAV. In addi-tional, the mathematical modeling to represent the physical movements could be classified as a topic, because it is possible to find different approaches and parametrization to simulate the behavior of UAV.
Drones swarms is classified as a topic in special because of the challenge that this area have been offer for the researches. It is possible to find different approaches in how to control a swarm, but the most of works founded present a solution that not preview fault tolerance and eventual problems in a real situations.
Because of the relevance, even with just one work, a comparison between the topologies was included in this work as a main topic. There is no more works this area, but in initial phases of the project it is important to have a survey containing details about what kind of drone is better for a specific application.
B. RQ2 - Is the results founded were satisfactory?
Regarding mathematical models, you can find different approaches may depend on the application, control, or the parameter chosen by the designer. All models found have the same base, the model Newton-Euler, but which differs from the models would be new forms of parametrization such as the quaternions, which avoids the usage patterns of the Newton-Euler model. The definition of mathematical model is the first
TABLE III
METHODS TO SOLVE THE PROBLEMS. Problem Method Mathematical Modelindg Physical laws, Quaternions
Control Systems PID, Fuzzy, Evolutionary Algorithms Drones Swarm Evolutionary Algorithms, Human interfaces UAV Performance Analytic
phase of the project from a controller of a UAV, it was possible to strengthen the models that were found in the works cited in the systematic review in other work related to the control design.
Another well comprehensive factor in relation to the UAV, is the control system design, this paper discussed different approaches, such as position control, trajectory, take off and landing. You can use different controllers, such as PID, fuzzy, PD, or even other smart algorithms to set paths or stability control. The UAV control area is already well established, most of the articles use the same approaches, not back more so scientific contribution the development of control. On the other hand this is important because in the view of designers, broad-based research is available, it is possible to know the behaviour of each controller before choosing the project.
There are different topologies for UAV, it is possible an-alytically deduce which of them is more stable, the battery consumption ratio, the behaviour of each to add a charge, as was done in the work [21], this is important for the initial steps of the design of a UAV.
The application for drone swarm has grown increasingly for different applications. In the context of this survey was treated approaches related to control swarms, but the area is wider and can find different opportunities for research, such as: wi-fi signal distribution, monitoring of a specific area, as it should cover a certain goal. The results for the UAVs swarm control have many limitations on unexpected situations.
Another important factor related to drone swarms is the question of sensing the shape of how the sensors are monitored is critical to the achievement of a goal. Control of the sensors also becomes a factor to be careful as can be inferred directly from the expected results, so that was cited in both the work this issue.
C. RQ3 - What are the methods used for solve the problems? For answer this question, the table III, present the methods used to solve the problems in each topic.
D. RQ4 - What are the challenges to be solved?
It is possible conclude that do not have much challenge in finding different approaches to mathematical models and control systems, as the results are clear in the bibliographies found. On the other hand, results in areas of the performance topologies and clusters still require a greater contribution.
In relation to the drones swarm, there are a lot of works trying to solve the challenge to control a swam for a specific mission. All the works used different methods, also these methods did not work as expected, but close in all the cases.
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This open the opportunities for new studies to find new ways to control, or improve the methods existent.
The results Comparison between the topologies of UAV are poor, the only work in this subarea focus in a analytics analysis, without any support in the results. Simulations and experiments considering different real situations that the UAV can pass on a path, such as instability caused by external forces. Another important factor is the fact that no studies comparing different headings for a given topology, such as quadcopter Plus and ’X’. In additional, there are not many works purposing studies to measure performance.
VI. DISCUSSION
The goal of this systematic review is identify the main methods used to solve different issues in Unnamed Aerial Vehicle, as well as their challenges and problems, in other words, identify how the studies with this focus are conducted and how solve the common problems. This section aims to clarify if the goal was achieved and point, as well as giving an overview of search questions.
A. Overview
It was observed that all the articles found in the survey data are relatively recent, and the oldest was published in 2006 and the latest in 2016. This reaffirms the question that technology is still very new, opening up many opportunities for research, and with many issues to be resolved. The Graphic 5 present a overview of the years of the references used in this survey.
Fig. 5. Relation between number of articles published and year
Being very recent publications, it is believed that still has much to develop, especially in the areas of swarms and performance analysis. Many recent publications have focused on the control area, an area already achieved results and little potential for innovation. The drones area has great flexibility to different topics of research, you can find more topics that did not fit for this data collection.
B. Collaboration
To our knowledge, this is the first systematic review with the objective to identify the problems and solutions in different
subareas of the UAV, maybe the first review of the theme. The method , challenges and problems and solutions was identified, difficult issues to be answered in a paper that focus in demonstrate a method and the effectiveness of each method. This work may contribute to focusing the research efforts in improve the design of aerial vehicles, and how control them. The SLR will helps scientists who are developing or researching to find new ways in the design step, showing the possibilities and problems in the literature, as well as the main studies and their methods. Information provided here will help the developers to improve the aerial and control design.
VII. CONCLUSION
It was done in this study a survey of what has been researched in UAVs area. The survey was done on the basis of the potential subjects of research in this area, in which case it was subdivided in mathematical modeling, control systems, drones swarm and finally a brief comparative in topologies. This technology is increasingly rising, and is found in different applications, thus presenting a great deal of research potential. The objective of this study was to contextualize each of the major research front, showing and commenting on the work that has been carried out and carry out a superficial analysis of the results, and discuss the coexistence of them. It is believed that the goal was achieved, based on the main found work and discussion about them: for this discussion opens the vision of designer and researcher, providing the initial steps forward research that will be chosen.
As a contribution of this work is expected to bring more information to work already carried out, as well as research areas that are deficient in the UAV area, such as a more detailed comparison between the topologies, and may be a future job with great potential.
REFERENCES
[1] R. C. Gomes and F. J. A. Aquino, Simulac¸˜ao de voo vertical de um quadric´optero usando software livre. Fortaleza: Instituto Federal de Educac¸˜ao, Ciˆencia e Tecnologia do Cear´a, 2008.
[2] J. D. Sousa, “Modelagem e identificac¸˜ao de um ve´ıculo a´ereo n˜ao tripulado do tipo quadrirotor,” Bras´ılia, 2014. [Online]. Available: https://fga.unb.br/articles/0000/7615/relatorio.pdf
[3] T. Luukkonen, “Modelling and control of quadcopter,” 2011. [4] V. M. Giordano Bruno Antoniazzi Ronconi, Tha´ıs Jessinski Batista,
“The utilization of unmanned aerial vehicles (uav) for military action in foreign airspace,” 2014.
[5] R. Austin, Unmanned Aircraft Systems UAV Design, Development and Deploment, 1st ed. The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom: Wiley, 2010.
[6] J. Roskam, Airplane flight dynamics and automatic flight controls - Part I. Lawrence, Unites States: DARcorporation, 2006.
[7] C. Martinello, “Comparativo entre controlador pid e fuzzy no controle de atitude em um quadric´optero,” 2014.
[8] J. A. Leishman, “The br´eguet-richet quadrotor helicopter of,” 2002. [9] N. M. Marulica, “Mathematical modeling of uav with four rotors,”
Interdisciplinary Description of Complex Systems, vol. 14, pp. 88–100, January 2016.
[10] A. Salih, M. Moghavvemi, H. Mohamed, and K. S. Gaeid, “Flight pid controller design for a uav quadrotor,” Scientific Research and Essays, vol. 5, pp. 3660–3667, 2010. [Online]. Available: https://www.researchgate.net/publication/230633819 Flight PID Controller Design for a UAV Quadrotor
[11] B. Kada and Y. Ghazzawi, “Robust pid controller design for an uav flight control system,” World Congress on Engineering and Computer Science, vol. 2, 2011. [Online]. Available: www.iaeng.org/publication/ WCECS2011/WCECS2011 pp945-950.pdf
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[12] V. Artale, C. Milazzo, and A. Ricciardello, “Mathematical modeling of hexacopter,” Applied Mathematical Sciences,, vol. 7, pp. 4805–4811, January 2013.
[13] F. A. Azis, R. Akmeliawati, and S. Ahmad, “Mathematical modelling of hexacopter system: A port-hamiltonion approach,” International Con-ference on Intelligent Unmanned Systems, vol. 11, 2015.
[14] J.-J. Xiong and En-HuiZheng, “Position and attitude tracking control for a quadrotor uav,” ISA Transactions, vol. 53, pp. 725–731, July 2014. [15] A. Sharma and A. Barve, “Controlling of quadrotor uav using pid
controller and fuzzy logic controller,” International Journal of Electrical, Electronics and Computer Engineering, vol. 2, pp. 28–41, September 2012.
[16] A. V., M. C., and A. Ricciardielo, “Pid controller applied to hexacopter flight,” Journal of Intelligent and Robotic Systems ˆA·, vol. 22, pp. 28–41, January 2014.
[17] S. Khantsis and A. Bourmistrova, “Uav controller design using evolutionary algorithms,” AI 2005: Advances in Artificial Intelligence, vol. 3809, pp. 1025–1030, 2005. [Online]. Available: http://link. springer.com/chapter/10.1007/11589990 134
[18] J. Bacik, D. Perdukova, and P. Fedor, “Design of fuzzy controller for hexacopter position control,” International Journal of Science and Research, vol. 347, pp. 193–200, November 2015.
[19] R. McCune and G. Madey, “Swarm control of uavs for cooperative hunt-ing with dddas,” International Conference on Computational Science, vol. 18, pp. 2537–2544, June 2013.
[20] A. Hocraffer and C. Nam, “A meta-analysis of human-system inter-faces in unmanned aerial vehicle (uav) swarm management,” Applied Ergonomics, vol. 58, pp. 66–80, 2016.
[21] K. Agrawal and P. Shrivastav, “Multi-rotors: A revolution in unmanned aerial vehicle,” International Journal of Science and Research, vol. 4, pp. 1800–1804, November 2015.
[22] B. Kada and Y. Ghazzawi, “Fuzzy logic based integrated controller for unmanned aerial vehicles,” Florida Conference on Recent Advances in Robotic, vol. 4, 2006.
[23] J. F. Gomez and M. Jamshidi, “Fuzzy adaptive control for a uav,” Journal of Intelligent Robotic Systems, vol. 62, 2011. [Online]. Available: link.springer.com/article/10.1007/s10846-010-9445-4
