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L2 Gain And Passivity Techniques In Nonlinear Control

Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult-to-access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.

Output Feedback Control of a Quadrotor UAV Using Neural Networks

Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges

Coverage path planning consists of finding the route which covers every point of a certain area of interest. In recent times, Unmanned Aerial Vehicles (UAVs) have been employed in several application domains involving terrain coverage, such as surveillance, smart farming, photogrammetry, disaster management, civil security, and wildfire tracking, among others. This paper aims to explore and analyze the existing studies in the literature related to the different approaches employed in coverage path planning problems, especially those using UAVs. We address simple geometric flight patterns and more complex grid-based solutions considering full and partial information about the area of interest. The surveyed coverage approaches are classified according to a classical taxonomy, such as no decomposition, exact cellular decomposition, and approximate cellular decomposition. This review also contemplates different shapes of the area of interest, such as rectangular, concave and convex polygons. The performance metrics usually applied to evaluate the success of the coverage missions are also presented.

Survey on Coverage Path Planning with Unmanned Aerial Vehicles

The objective of this paper is to generate a desired flight path to be followed by an aerial robot. A curve with discontinuous curvature and torsion is not appropriate for smooth motions for any vehicle architecture. The flyable path should be smooth, i.e. without twists and cusps. The smoothness of the path is determined by amount of bending of the path, measured by curvature and torsion of the path. Three different classes of curves are presented. First, constant curvature and torsion followed by a linear variation versus the curvilinear abscissa then a quadratic variation. Finally, the problem of manoeuvre between two trim helices of different curvature and torsion is tackled.

3D curves with a prescribed curvature and torsion for an aerial robot

Motion generation gives the joint positions speeds and accelerations of manipulators, at every moment. We assume that the motion are polynomial trajectories, that ensure joint acceleration continuity Usual kinematical constraints, obtained with approximations, are not always sufficient, then we will focus on actuators constraints on voltages and currents.

Polynomial motion generation of manipulators with technological constraints

Cartesian positions, speeds and accelerations are planned to describe the desired motion of manipulators. We examine the case of point to point motions, assuming that the reference values of the manipulator are represented by C 2 polynomial trajectories. Usual kinematical constraints are not always sufficient, then we focus on voltage and current DC actuator constraints. A minimun time motion generation problem is solved by means of the resolution of some polynomial equations.

A motion generation method of manipulators for cartesian paths

In this study, our aim is to propose an approach to generate the global trajectory an airplane must follow during its mission. In this approach, the problem of piloting an autonomous airplane is treated in two stages: generate and follow the reference trajectory. The first problem is rather an optimization problem with constraints; the second is a problem of control. Toward this aim, we decompose the global trajectory into a set of four elementary trajectories (horizontal level flight, climb, descent and horizontal turn). The second problem to be treated is the interconnection between these elementary trajectories. For this the airplane must follow a non trim trajectory. In this article, we start by defining the two dynamic constraints of equality type related to the under actuation (two differential equations), then we introduce the concept of (permanent) trim trajectories and the (transitional) non trim trajectories. Then, for the first type, we formulate an optimization problem with constraints, minimizing the necessary time for each elementary trajectory; for the transitional trajectories, we solve the equations of underactuation.

A new approach to trajectories planner design for a subsonic autonomous aerial fixed wing vehicle

The optimal motion generation problem is solved subject to actuator constraints while the motion is constrained to an arbitrary path. The considered objective function is a weighted time energy function. Existing methods consider only the time-optimal problem. We present some simulation results using a mathematical programming technique (sequential quadratic programming) existing in the NPSOL software. Then, a comparative study is made between existing methods and the proposed technique. >

http://ieeexplore.ieee.org/iel2/3184/9021/00400249.pdf

Yasmina Bestaoui

Papers

3D curves with a prescribed curvature and torsion for an aerial robot

Polynomial motion generation of manipulators with technological constraints

A motion generation method of manipulators for cartesian paths

A new approach to trajectories planner design for a subsonic autonomous aerial fixed wing vehicle

A comparative study of optimal control algorithms for robot continuous path planning