Computer Simulation of Automatic Control of an Agricultural Small Unmanned Aerial Vehicle with Variable Mass

The stability control of unmanned aerial vehicle (UAV) is the most important technology when it is on the duty of taking area photos. This paper aims at analyzing the structures, the corresponding channel of control and control modes in small fixed-wing UAV, and focuses on flight control system, which systematically reveals the running rules of UAV. According to the control theories in UVA, the paper explains the method of stability controlling UAV from two major aspects, the longitudinal and lateral movement control, based on the UAV flight operation process. By understanding the structures, the modes, the rules and the theories, the paper achieves the goal that can catch the method of fully controlling UAV.

ABSTRACT. Changes in lift and thrust were elicited in tethered male gypsy moths, Lymantria dispar L. (Lepidoptera, Lymantriidae), by visual pattern elements moving radially either towards or from the point directly beneath their body, if the sex‐pheromone, (+)‐disparlure, was present. The sign of these changes was such as to counteract the pattern movements, which were generated by a rotating spiral beneath the moth. By restricting the area of spiral visible to the moth to either transverse or longitudinal sectors, flight altitude was affected by the centrifugal/centripetal movements in the lateral sectors, whereas flight speed was affected by those in the frontal sector. It is deduced that in free flight these compensatory reactions are responsible for the stabilization of flight altitude and speed, respectively. Surprisingly, without pheromone present these responses were usually not detectable: a wide range of flight altitude and speed was then observed. In the presence of (+)‐disparlure, however, these responses were always strongly pronounced, the animal keeping within a narrow range of speed and altitude. These compensatory reactions were blocked by the attraction‐inhibiting (‐)‐disparlure if presented in racemic mixture with the (+) form: the range of speed and altitude shown by the moth was then the same as without any pheromone. Under closed‐loop conditions, the mean flight speed was reduced by the racemic mixture as well as by (+)‐disparlure alone, however.

In this paper we discuss the design issues and the corresponding systematic sequence of events related to a basic controller for an Unmanned Aerial Vehicle (UAV). To this end, we first present the details of a basic PID controller, We then describe the equations and investigate the problems of how these equations will be approximated for determining the dynamic longitudinal movement of UAV. After specifying the model of the system and clarifying the details of the designed algorithms, we will identify the gains corresponding to the coefficients of the PID controller using the well-known AeroSim simulator software. The computed gains and the results drawn from the simulation process will be used to analyze the UAV stability against important metrics such as air speed and pitch angle.

Small unmanned aerial vehicles (UAVs) can provide facilities in various applications. Compared with single UAV system, small UAVs based cooperative UAV system can bring advantages such as higher efficiency and safety. Therefore, it is necessary to design a robust multi-agent cooperative flight controller to coordinate a group of small UAVs for stable formation flights. This paper investigates the problem of consensus-based formation control for a multi-UAV system. Firstly, We choose a simplified model with nonholonomic constraints for UAV dynamics. Secondly, using the algebraic theory and backstepping technique, we design consensus protocols for multi-UAV systems under the strongly connected topology. Then based on that, we propose a multi-UAVfromation control strategy. Finally, we extend our results to the directed topology case which is still effective by simulation.

The present PhD thesis addresses the problem of the control of small fixed-wing Unmanned Aerial Vehicles (UAVs). In the scientific community much research is dedicated to the study of suitable control laws for this category of aircraft. This interest is motivated by the several applications that these platforms can perform and by their peculiarities as dynamical systems. In fact, small UAVs are characterized by highly nonlinear behavior, strong coupling between longitudinal and latero-directional planes, and high sensitivity to external disturbances and to parametric uncertainties. Furthermore, the challenge is increased by the limited space and weight available for the onboard electronics. The aim of this PhD thesis is to provide a valid confrontation among three different control techniques and to introduce an innovative autopilot configuration suitable for the unmanned aircraft field. Three advanced controllers for fixed-wing unmanned aircraft vehicles are designed and implemented: PID with H1 robust approach, L1 adaptive controller and nonlinear backstepping controller. All of them are analyzed from the theoretical point of view and validated through numerical simulations with a mathematical UAV model. One is implemented on a microcontroller board, validated through hardware simulations and tested in flight. The PID with H1 robust approach is used for the definition of the gains of a commercial autopilot. The proposed technique combines traditional PID control with an H1 loop shaping method to assess the robustness characteristics achievable with simple PID gains. It is demonstrated that this hybrid approach provides a promising solution to the problem of tuning commercial autopilots for UAVs. Nevertheless, it is clear that a tradeoff between robustness and performance is necessary when dealing with this standard control technique. The robustness problem is effectively solved by the adoption of an L1 adaptive controller for complete aircraft control. In particular, the L1 logic here adopted is based on piecewise constant adaptive laws with an adaptation rate compatible with the sampling rate of an autopilot board CPU. The control scheme includes an L1 adaptive controller for the inner loop, while PID gains take care of the outer loop. The global controller is tuned on a linear decoupled aircraft model. It is demonstrated that the achieved configuration guarantees satisfying performance also when applied to a complete nonlinear model affected by uncertainties and parametric perturbations. The third controller implemented is based on an existing nonlinear backstepping technique. A scheme for longitudinal and latero-directional control based on the combination of PID for the outer loop and backstepping for the inner loop is proposed. Satisfying results are achieved also when the nonlinear aircraft model is perturbed by parametric uncertainties. A confrontation among the three controllers shows that L1 and backstepping are comparable in terms of nominal and robust performance, with an advantage for L1, while the PID is always inferior. The backstepping controller is chosen for being implemented and tested on a real fixed-wing RC aircraft. Hardware-in-the-loop simulations validate its real-time control capability on the complete nonlinear model of the aircraft adopted for the tests, inclusive of sensors noise. An innovative microcontroller technology is employed as core of the autopilot system, it interfaces with sensors and servos in order to handle input/output operations and it performs the control law computation. Preliminary ground tests validate the suitability of the autopilot configuration. A limited number of flight tests is performed. Promising results are obtained for the control of longitudinal states, while latero-directional control still needs major improvements

In recent research works, morphing wings were studied as an interesting field for a small unmanned aerial vehicle (UAV). The previous studies either focused on selecting suitable material for the morphing wings or performing experimental tests on UAVs with morphing wings. Though, the dynamic modeling of active flexible morphing wings and their involved interactions with the aerodynamics of the UAV body are challenging subjects. Using such a model to control a small UAV to perform specific maneuvering is not investigated yet. The dynamic model of UAV with active morphing wings generates a multi-input multi-output (MIMO) system which rises the difficulty of the control system design. In this paper, the aeroelastic dynamic model of morphing wing activated by piezocomposite actuators is established using the finite element method and modal decomposition technique. Then, the dynamic model of the UAV is developed taking into consideration the coupling between the wing and piezocomposite actuators, as well as the dynamic properties of the morphing actuators with the aerodynamic wind disturbances. A model predictive control (MPC) is designed for the MIMO control system to perform specific flight maneuvering by tracking desired trajectories of UAV altitude and yaw angle. Additionally, the MPC achieves constrained behavior of pitch and roll angles to get satisfactory UAV motion. Also, the behaviors of the UAV control system using MPC are evaluated after adding Dryden wind turbulence to the UAV outputs. Finally, a UAV flight simulation is conducted which shows that the control system successfully rejects the applied disturbances and tracks the reference trajectories with acceptable behavior of pitch and roll angles.

Most of the recent research on distributed formation control of unmanned aerial vehicle (UAV) swarms is founded on position, distance, and displacement-based approaches; however, a very promising approach, i.e., bearing-based formation control, is still in its infancy and needs extensive research effort. In formation control problems of UAVs, Euler angles are mostly used for orientation calculation, but Euler angles are susceptible to singularities, limiting their use in practical applications. This paper proposed an effective method for time-varying velocity and orientation leader agents for distributed bearing-based formation control of quadcopter UAVs in three-dimensional space. It combines bearing-based formation control and quaternion-based attitude control using undirected graph topology between agents without the knowledge of global position and orientation. The performance validation of the control scheme was done with numerical simulations, which depicted that UAV formation achieved the desired geometric pattern, translation, scaling, and rotation in 3D space dynamically.

For the control of unmanned aerial vehicles (UAVs) in GPS-denied environments, cameras have been widely exploited as the main sensory modality for addressing the UAV state estimation problem. However, the use of visual information for ego-motion estimation presents several theoretical and practical difficulties, such as data association, occlusions, and lack of direct metric information when exploiting monocular cameras. In this paper, we address these issues by considering a quadrotor UAV equipped with an onboard monocular camera and an inertial measurement unit (IMU). First, we propose a robust ego-motion estimation algorithm for recovering the UAV scaled linear velocity and angular velocity from optical flow by exploiting the so-called continuous homography constraint in the presence of planar scenes. Then, we address the problem of retrieving the (unknown) metric scale by fusing the visual information with measurements from the onboard IMU. To this end, two different estimation strategies are proposed and critically compared: a first exploiting the classical extended Kalman filter (EKF) formulation, and a second one based on a novel nonlinear estimation framework. The main advantage of the latter scheme lies in the possibility of imposing a desired transient response to the estimation error when the camera moves with a constant acceleration norm with respect to the observed plane. We indeed show that, when compared against the EKF on the same trajectory and sensory data, the nonlinear scheme yields considerably superior performance in terms of convergence rate and predictability of the estimation. The paper is then concluded by an extensive experimental validation, including an onboard closed-loop control of a real quadrotor UAV meant to demonstrate the robustness of our approach in real-world conditions.

Computational fluid dynamics analysis of aerodynamic characteristics in long-endurance unmanned aerial vehicles

The constrained control of unmanned aerial vehicles (UAVs) is a challenging task due to their nonlinear and underactuacted dynamics. This brief focuses on the position control of a quadrotor UAV with state and input constraints using an inner–outer loop control structure. The outer loop generates a saturated thrust, and the reference roll and pitch angles, while the inner loop is designed to follow these reference angles using a traditional PID controller. Assuming perfect inner loop tracking, the outer loop nested saturation controller guarantees global asymptotic stability for output regulation and tracking. The effect of nonideal inner loop tracking on closed-loop stability is analyzed. The proposed method is experimentally validated on an indoor quadrotor platform.

Purpose Autonomous flight of unmanned aerial vehicles (UAVs) in global position system (GPS)-denied environments has become an increasing research hotspot. This paper aims to realize the indoor fixed-point hovering control and autonomous flight for UAVs based on visual inertial simultaneous localization and mapping (SLAM) and sensor fusion algorithm based on extended Kalman filter. Design/methodology/approach The fundamental of the proposed method is using visual inertial SLAM to estimate the position information of the UAV and position-speed double-loop controller to control the UAV. The motion and observation models of the UAV and the fusion algorithm are given. Finally, experiments are performed to test the proposed algorithms. Findings A position-speed double-loop controller is proposed, by fusing the position information obtained by visual inertial SLAM with the data of airborne sensors. The experiment results of the indoor fixed-points hovering show that UAV flight control can be realized based on visual inertial SLAM in the absence of GPS. Originality/value A position-speed double-loop controller for UAV is designed and tested, which provides a more stable position estimation and enabled UAV to fly autonomously and hover in GPS-denied environment.

*† ‡ § Applications of aerial surveillance include homeland security, law enforcement, environmental monitoring, and damage inspection after natural disasters. This paper discusses the use of unmanned aerial vehicles (UAV) as low cost and easy to operate solutions for aerial reconnaissance. Currently, the use of UAVs is limited by the cost of the systems and the need for skilled operators of the equipment. A new flight control system was developed which will reduce the cost of autonomous UAV platforms. The emphasis of the flight controller design was to reduce the cost of implementing an unmanned aerial surveillance system. The costs were reduced two ways. First, the weight and volume of the flight control and payload hardware was reduced so that smaller UAVs could be used. Second, the cost of the hardware was decreased by using standard commercial off-the-shelf (COTS) components to build the hardware. This paper will cover the requirements of the autonomous flight control and payload system for aerial surveillance, the work done to reduce the weight of the system, and the selection of COTS hardware for the flight controller. Flight control for the aerial surveillance platform is divided into four parts: instrumentation, control, communication, and power. The UAV control system designed supports autonomous flight including takeoff and landing which eliminates the need for a skilled RC pilot to operate the system. The system is designed specifically for applications with shorter flights within three to five miles of the ground station. GPS and inertial measurement sensors localize the UAV and are inputs in the flight control algorithm. A wireless communication link between the UAV and the ground station receives flight commands and waypoints from the mission planner and transmits status monitoring information. A safety pilot can manually override the autonomous flight controller with an RC communication link. Aerial surveillance payloads include a system to collect and wirelessly transmit video. Many also have a pan-tilt-zoom unit to position the camera to get video from different orientations. Several applications also require analog sensors and/or other digital I/O. Lowering the flight controller and payload weight to use smaller UAVs and using COTS parts in the design reduced the cost of implementing an aerial surveillance system. Using smaller UAVs reduced the vehicle platform costs by a factor of three to five. Integrating the flight control hardware and the payload support hardware was the primary way the weight was reduced. Many of the components in one system were duplicated in the other. Eliminating the duplicate parts and subsystems lowered the component weight and volume (thus reducing the packaging weight). This also helps decrease the hardware costs without sacrificing the function of the flight controller or aerial surveillance payload. All of the components are standard COTS parts with the exception of the printed circuit boards.

: Unmanned aerial vehicles (UAVs) are critical components of the future naval forces. UAV control and monitoring with autonomous operation will become an absolute necessity and adaptive cooperation of vehicles is the only practical alternative. The objective of this project is to develop and evaluate new methodologies for cooperative (formation) control of multiple unmanned air vehicles. The goal is to have multiple UAVs working together as a group. Instead of separately assigning distinct tasks to each vehicle, the operator would assign tasks to the UAV group, which then determines the best way to accomplish each task, freeing the operator to maintain surveillance over the entire operation. In this project we investigated Path Tracking and obstacle avoidance of UAVs using fuzzy logic method. Algorithms for close formation control of multi-UAVs are developed and simulated. We also investigated fault-tolerant control of single UAVs by neuro-adaptive method. Detailed description of this method is provided in this document. The project has supported S graduate students with 9 technical papers published.

This paper presents a robust kinematic control of unmanned UAV aerial vehicles with non-holonomic constraints. The studied system consists of a 2D UAV non-holonomic kinematic model represented as a driftless system with its state and control inputs. The first part of this study consists of the evidence that the model being studied is non-holonomic in view of its involutivity properties. The second part of this study consists of the design of a robust kinematic controller for an unmanned aerial vehicle (UAV) in which the states of the systems are used for feedback control and the desired angular and linear velocities are precisely tracked by the proposed controller approach. This control strategy is achieved by designing the appropriate Lyapunov functional to meet the robust stability conditions and by finding the switching gains to track the desired profile. The control strategy obtained is tested in the proposed 2D mathematical model of the unmanned aerial vehicle and it is confirmed that the system variables track the desired profile while keeping the angular and linear velocity bounded. This study concludes with a discussion of the results and the respective conclusions.

Nowadays, there are many researches on UAV (Unmanned Aerial Vehicle) control systems for disaster monitoring, national defense and surveillance applications, which mainly focus on flight performance of UAV or multiple UAV control by single operator. This paper presents design and implementation of an effective system for multiple operators to control UAVs based on RBAC (Role Based Access Control). In the proposed system, a UAV is connected to the UAV control server, and operators remotely access to the UAV by connecting to the server using various devices such as smart phones, desktops, and laptops at the same time. Each operator can control the UAV based on RBAC, in other words, operators are granted with permissions which are corresponding to the given roles. For example, the administrator may have all the permissions defined in the system and a pilot has a role where the flight control and flight status permissions are granted. In addition, operators may have a role with the camera tilt control and video access permissions. The major advantage of RBAC-based approach is to prevent unnecessary operational confusion, conflict and mistake under multi-operator UAV environments. Another advantage is to increase efficiency and accuracy of UAV mission control by allowing a mission to be decomposed into specific roles.