Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Hybrid active force control for fixed based rotorcraft

Disturbances are considered major challenges faced in the deployment of rotorcraft unmanned aerial vehicle (UAV) systems. Among different types of rotorcraft systems, the twin-rotor helicopter and quadrotor models are considered the most versatile flying machines nowadays due to their range of applications in the civilian and military sectors. However, these systems are multivariate and highly non-linear, making them difficult to be accurately controlled. Their performance could be further compromised when they are operated in the presence of disturbances or uncertainties. This dissertation presents an innovative hybrid control scheme for rotorcraft systems to improve disturbance rejection capability while maintaining system stability, based on a technique called active force control (AFC) via simulation and experimental works. A detailed dynamic model of each aerial system was derived based on the Euler–Lagrange and Newton-Euler methods, taking into account various assumptions and conditions. As a result of the derived models, a proportional-integral-derivative (PID) controller was designed to achieve the required altitude and attitude motions. Due to the PID's inability to reject applied disturbances, the AFC strategy was incorporated with the designed PID controller, to be known as the PID-AFC scheme. To estimate control parameters automatically, a number of artificial intelligence algorithms were employed in this study, namely the iterative learning algorithm and fuzzy logic. Intelligent rules of these AI algorithms were designed and embedded into the AFC loop, identified as intelligent active force control (IAFC)-based methods. This involved, PID-iterative learning active force control (PID-ILAFC) and PID-fuzzy logic active force control (PID-FLAFC) schemes. To test the performance and robustness of these proposed hybrid control systems, several disturbance models were introduced, namely the sinusoidal wave, pulsating, and Dryden wind gust model disturbances. Integral square error was selected as the index performance to compare between the proposed control schemes. In this study, the effectiveness of the PID-ILAFC strategy in connection with the body jerk performance was investigated in the presence of applied disturbance. In terms of experimental work, hardware-in-the-loop (HIL) experimental tests were conducted for a fixed-base rotorcraft UAV system to investigate how effective are the proposed hybrid PID-ILAFC schemes in disturbance rejection. Simulated results, in time domains, reveal the efficacy of the proposed hybrid IAFC-based control methods in the cancellation of different applied disturbances, while preserving the stability of the rotorcraft system, as compared to the conventional PID controller. In most of the cases, the simulated results show a reduction of more than 55% in settling time. In terms of body jerk performance, it was improved by around 65%, for twin-rotor helicopter system, and by a 45%, for quadrotor system. To achieve the best possible performance, results recommend using the full output signal produced by the AFC strategy according to the sensitivity analysis. The HIL experimental tests results demonstrate that the PID-ILAFC method can improve the disturbance rejection capability when compared to other control systems and show good agreement with the simulated counterpart. However, the selection of the appropriate learning parameters and initial conditions is viewed as a crucial step toward this improved performance

Proceedings of the International Micro Air Vehicles Conference and Flight Competition 2017 (IMAV 2017)

The IMAV 2017 conference has been held at ISAE-SUPAERO, Toulouse, France from Sept. 18 to Sept. 21, 2017. More than 250 participants coming from 30 different countries worldwide have presented their latest research activities in the field of drones. 38 papers have been presented during the conference including various topics such as Aerodynamics, Aeroacoustics, Propulsion, Autopilots, Sensors, Communication systems, Mission planning techniques, Artificial Intelligence, Human-machine cooperation as applied to drones

A Survey on Aerial Swarm Robotics

The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas

Rotorcraft Blade Pitch Control Through Torque Modulation

Micro air vehicle (MAV) technology has broken with simple mimicry of manned aircraft in order to fulfill emerging roles which demand low-cost reliability in the hands of novice users, safe operation in confined spaces, contact and manipulation of the environment, or merging vertical flight and forward flight capabilities. These specialized needs have motivated a surge of new specialized aircraft, but the majority of these design variations remain constrained by the same fundamental technologies underpinning their thrust and control. This dissertation solves the problem of simultaneously governing MAV thrust, roll, and pitch using only a single rotor and single motor. Such an actuator enables new cheap, robust, and light weight aircraft by eliminating the need for the complex ancillary controls of a conventional helicopter swashplate or the distributed propeller array of a quadrotor. An analytic model explains how cyclic blade pitch variations in a special passively articulated rotor may be obtained by modulating the main drive motor torque in phase with the rotor rotation. Experiments with rotors from 10 cm to 100 cm in diameter confirm the predicted blade lag, pitch, and flap motions. We show the operating principle scales similarly as traditional helicopter rotor technologies, but is subject to additional new dynamics and technology considerations. Using this new rotor, experimental aircraft from 29 g to 870 g demonstrate conventional flight capabilities without requiring more than two motors for actuation. In addition, we emulate the unusual capabilities of a fully actuated MAV over six degrees of freedom using only the thrust vectoring qualities of two teetering rotors. Such independent control over forces and moments has been previously obtained by holonomic or omnidirection multirotors with at least six motors, but we now demonstrate similar abilities using only two. Expressive control from a single actuator enables new categories of MAV, illustrated by experiments with a single actuator aircraft with spatial control and a vertical takeoff and landing airplane whose flight authority is derived entirely from two rotors

Flight Control of a Millimeter-Scale Flapping-Wing Robot

Flying insects display remarkable maneuverability. Unlike typical airplanes, these insects are able to execute an evasive action, rapidly change their flight speed and direction, or leisurely land on flowers buffeted by wind, exhibiting aerodynamic feats unmatched by any state-of-the-art aircraft. By subtly tuning their wing motions, they generate and manipulate unsteady aerodynamic phenomenon that is the basis of their extraordinary maneuverability. Inspired by these tiny animals, scientists and engineers have pushed the boundaries of technology in many aspects, including meso-scale fabrication, electronics, and artificial intelligence, to develop autonomous millimeter-scale flapping-wing robots. In this thesis, we demonstrate, on real insect-scale robots, that using only an approximate model of the aerodynamics and flight dynamics in combination with conventional tools in nonlinear control, the inherently unstable flapping-wing robot can achieve steady hover. We present the development of flight controllers that gradually enhance the flight precision, allowing the robot to realize increasingly aggressive trajectories, including a highly acrobatic maneuver---perching on a vertical surface, as observed in its natural counterparts. We also demonstrate that these experiments lead to higher fidelity of in-flight aerodynamic models, strengthening our understanding of the dynamics of the robot and real insects.Engineering and Applied Science

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

Application of Norm Optimal Iterative Learning Control to Quadrotor Unmanned Aerial Vehicle for monitoring overhead power system

Wind disturbances and noise severely affect Unmanned Aerial Vehicles (UAV) when monitoring and find in faults in overhead power lines. Accordingly, we propose repetitive learning as a new solution for the problem. In particular, the performance of Iterative Learning Control (ILC)that are based on optimal approaches are examined, namely (i) Gradient-based ILC and (ii) Norm Optimal ILC. When considering the repetitive nature of fault-findin tasks for electrical overhead power lines, this study develops, implements and evaluates optimal ILC algorithms for a UAV model.Moreover, we suggest attempting a learning gain variation on the standard optimal algorithms instead of heuristically selecting from the previous range. The results of both simulations and experiments o gradient-based norm optimal control reveal that the proposed ILC algorithm has not only contributed to good trajectory tracking, but also good convergence speed and the ability to cope with exogenous disturbances such as wind gusts

A survey of free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle

The objective of this paper is to analyze free software for the design, analysis, modelling, and simulation of an unmanned aerial vehicle (UAV). Free software is the best choice when the reduction of production costs is necessary; nevertheless, the quality of free software may vary. This paper probably does not include all of the free software, but tries to describe or mention at least the most interesting programs. The first part of this paper summarizes the essential knowledge about UAVs, including the fundamentals of flight mechanics and aerodynamics, and the structure of a UAV system. The second section generally explains the modelling and simulation of a UAV. In the main section, more than 50 free programs for the design, analysis, modelling, and simulation of a UAV are described. Although the selection of the free software has been focused on small subsonic UAVs, the software can also be used for other categories of aircraft in some cases; e.g. for MAVs and large gliders. The applications with an historical importance are also included. Finally, the results of the analysis are evaluated and discussed—a block diagram of the free software is presented, possible connections between the programs are outlined, and future improvements of the free software are suggested. © 2015, CIMNE, Barcelona, Spain.Internal Grant Agency of Tomas Bata University in Zlin [IGA/FAI/2015/001, IGA/FAI/2014/006