2,301 research outputs found

    MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

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    In this work, a new pre-tuning multivariable PID (Proportional Integral Derivative) controllers method for quadrotors is put forward. A procedure based on LQR/LQG (Linear Quadratic Regulator/Gaussian) theory is proposed for attitude and altitude control, which suposes a considerable simplification of the design problem due to only one pretuning parameter being used. With the aim to analyze the performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, together with sensors drift/bias properties and noise characteristics of low-cost commercial sensors typically used in this type of applications are considered. In order to estimate the state vector and compensate bias/drift effects in the measures, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robustness analysis of the control system is carried out by employing numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show the proposed controller design method for multivariable PID controller is robust with respect to: (a) parametric uncertainty in the plant model, (b) disturbances acting at the plant input, (c) sensors measurement and estimation errors

    Suspended Load Path Tracking Control Using a Tilt-rotor UAV Based on Zonotopic State Estimation

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    This work addresses the problem of path tracking control of a suspended load using a tilt-rotor UAV. The main challenge in controlling this kind of system arises from the dynamic behavior imposed by the load, which is usually coupled to the UAV by means of a rope, adding unactuated degrees of freedom to the whole system. Furthermore, to perform the load transportation it is often needed the knowledge of the load position to accomplish the task. Since available sensors are commonly embedded in the mobile platform, information on the load position may not be directly available. To solve this problem in this work, initially, the kinematics of the multi-body mechanical system are formulated from the load's perspective, from which a detailed dynamic model is derived using the Euler-Lagrange approach, yielding a highly coupled, nonlinear state-space representation of the system, affine in the inputs, with the load's position and orientation directly represented by state variables. A zonotopic state estimator is proposed to solve the problem of estimating the load position and orientation, which is formulated based on sensors located at the aircraft, with different sampling times, and unknown-but-bounded measurement noise. To solve the path tracking problem, a discrete-time mixed H2/H\mathcal{H}_2/\mathcal{H}_\infty controller with pole-placement constraints is designed with guaranteed time-response properties and robust to unmodeled dynamics, parametric uncertainties, and external disturbances. Results from numerical experiments, performed in a platform based on the Gazebo simulator and on a Computer Aided Design (CAD) model of the system, are presented to corroborate the performance of the zonotopic state estimator along with the designed controller

    Optimization of Nano-Rotor Blade Airfoil Usinf Controlled Elitist NSGA-II

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    The aerodynamic performance of airfoil at ultra-low Reynolds number has a great impact on the propulsive performance of nano rotor. Therefore, the optimization of airfoil is necessary before the design of nano rotor. Nano rotor blade airfoil optimization is a multi-objective problem since the airfoil suffers a wide range of Reynolds number which increases the difficulty of optimization. In this paper, the airfoil of nano rotor was optimized based on the controlled elitist Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupling with the parameterization method of Class function/Shape function Transformation technique (CST) and the multi-objectives function processing method of statistical definition of stability. An airfoil was achieved with the thickness of 2% and the maximum camber of 5.6% at 2/3 of chord. Airfoil optimized exhibits a good aerodynamic performance at ultra-low Reynolds number according to the computational results. And comparisons were carried out between the performance of the rotor designed with airfoil optimized and that of the rotor designed with AG38 airfoil, which showed that the airfoil optimized was suitable for rotor design

    Design and control of next-generation uavs for effectively interacting with environments

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    In this dissertation, the design and control of a novel multirotor for aerial manipulation is studied, with the aim of endowing the aerial vehicle with more degrees of freedom of motion and stability when interacting with the environments. Firstly, it presents an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. The effectiveness of this method is demonstrated through simulation. Secondly, a humanoid robot arm is adopted to serve as a 6-degree-of-freedom (DOF) automated flight testing platform for emulating the free flight environment of UAVs while ensuring safety. Another novel multirotor in a tilt-rotor architecture is studied and tested for coping with parametric uncertainties in aerial maneuvering and manipulation. Two pairs of rotors are mounted on two independently-controlled tilting arms placed at two sides of the vehicle in a H configuration to enhance its maneuverability and stability through an adaptive robust control method. In addition, an impedance control algorithm is deployed in the out loop that modifies the trajectory to achieve a compliant behavior in the end-effector space for aerial drilling and screwing tasks

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

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    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

    Model Predictive Control for Micro Aerial Vehicles: A Survey

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    This paper presents a review of the design and application of model predictive control strategies for Micro Aerial Vehicles and specifically multirotor configurations such as quadrotors. The diverse set of works in the domain is organized based on the control law being optimized over linear or nonlinear dynamics, the integration of state and input constraints, possible fault-tolerant design, if reinforcement learning methods have been utilized and if the controller refers to free-flight or other tasks such as physical interaction or load transportation. A selected set of comparison results are also presented and serve to provide insight for the selection between linear and nonlinear schemes, the tuning of the prediction horizon, the importance of disturbance observer-based offset-free tracking and the intrinsic robustness of such methods to parameter uncertainty. Furthermore, an overview of recent research trends on the combined application of modern deep reinforcement learning techniques and model predictive control for multirotor vehicles is presented. Finally, this review concludes with explicit discussion regarding selected open-source software packages that deliver off-the-shelf model predictive control functionality applicable to a wide variety of Micro Aerial Vehicle configurations

    Trajectory tracking of quaternion based quadrotor using model predictive control

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    The aim of this paper is to introduce the trajectory tracking with a quaternion based quadrotor operation using model predictive con-trol (MPC). Since the efficacy of MPC on a system under noise and disturbance has been distinguished, it is a fair and successful attempt to apply MPC on the quaternion based quadrotor, which is a quite well-known system with uncertainties during operation. Quaternion approaches singularity-free orientation that is advantageous to design any trajectory for quadrotor wherein roll or pitch angle reaches at 90o. As a quaternion, with its four-tuple characteristics that incorporate vector elements, is different from Euler-angle orientation, a new cost function has been developed for the respective MPC controller. In order to achieve singularity-free ori-entations and abate the model infidelity of the system, the quaternion and MPC algorithm have been incorporated for quadrotor flight. Simulation based results elucidate the success of trajectory tracking of quaternion based dynamics of quadrotor using MPC approach

    System identification and model-based flight control system design for an agile maneuvring quadrotor platform

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    In this paper, we provide a system identification, model stitching and model-based flight control system design methodology for an agile maneuvering quadrotor micro aerial vehicle (MAV) technology demonstrator platform. The proposed MAV is designed to perform agile maneuvers in hover/low-speed and fast forward flight conditions in which significant changes in system dynamics are observed. As such, these significant changes result in considerable loss of performance and precision using classical hover or forward flight model based controller designs. To capture the changing dynamics, we consider an approach which is adapted from the full-scale manned aircraft and rotorcraft domain. Specifically, linear mathematical models of the MAV in hover and forward flight are obtained by using the frequency-domain system identification method and they are validated in time-domain. These point models are stitched with the trim data and quasi-nonlinear mathematical model is generated for simulation purposes. Identified linear models are used in a multi objective optimization based flight control system design approach in which several handling quality specifications are used to optimize the controller parameters. Lateral reposition and longitudinal depart/abort mission task elements from ADS-33E-PRF are scaled-down by using kinematic scaling to evaluate the proposed flight control systems. Position hold, trajectory tracking and aggressiveness analysis are performed, Monte-Carlo simulations and actual flight test results are compared. The results show that the proposed methodology provides high precision and predictable maneuvering control capability over an extensive speed envelope in comparison to classical control techniques. Our current work focuses on i) extension of the flight envelope of the mathematical model and ii) improvement of agile maneuvering capability of the MAV
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