scholarly journals Optimal design of Vertical-Taking-Off-and-Landing UAV wing using multilevel approach

2020 ◽  
Vol 11 ◽  
pp. 26
Author(s):  
Hao Yue ◽  
David Bassir ◽  
Hicham Medromi ◽  
Hua Ding ◽  
Khaoula Abouzaid
Keyword(s):  
Optimization Problem ◽  
Delta Wing ◽  
Optimization Approach ◽  
Multilevel Optimization ◽  
Distribution Strategy ◽  
Surface Method ◽  
Flight Mode ◽  
Aerial Vehicle ◽  
Computational Fluid Dynamics Cfd ◽  
Cruise Flight

In order to overcome the propre disadvantages of FW(Fixed-Wing) and VTOL(Vertical-Taking-Off-and-Landing) UAV (Unmanned Aerial Vehicle) and extend its application, the hybrid drone is invested more in recent years by researchers and several classifications are developed on the part of dual system. In this article, an innovative hybrid UAV is raised and studied by introducing the canard configuration that is coupled with conventional delta wing as well as winglet structure. Profited by Computational Fluid Dynamics (CFD) and Response Surface Method (RSM), a multilevel optimization approach is practically presented and concerned in terms of cruise flight mode: adopted by an experienced-based distribution strategy, the total lift object is respectively assigned into the delta wing (90–95%) and canard wing(5–10%) which is applied into a two-step optimization: the first optimization problem is solved only with the parameters concerned with delta wing afterwards the second optimization is successively concluded to develop the canard configuration considering the optimized delta wing conception. Above all, the optimal conceptual design of the delta and canard wing is realized by achieving the lift goal with less drag performance in cruise mode.

Design space optimisation of an unmanned aerial vehicle submerged inlet through the formulation of a data-fusion-based hybrid model

2021 ◽  
pp. 1-18
Author(s):  
F. Akram ◽  
H. A. Khan ◽  
T. A. Shams ◽  
D. Mavris
Keyword(s):  
Data Mining ◽  
Data Fusion ◽  
Design Space ◽  
Design Parameters ◽  
Design Variables ◽  
Current Design ◽  
Aerial Vehicle ◽  
Hybrid Data ◽  
Computational Fluid Dynamics Cfd ◽  
Cruise Flight

ABSTRACT The research focuses on the design space optimisation of National Advisory Committee for Aeronautics (NACA) submerged inlets through the formulation of a hybrid data fusion methodology. Submerged inlets have drawn considerable attention owing to their potential for good on-design performance, for example during cruise flight conditions. However, complexities due to the geometrical topology and interactions among various design variables remain a challenge. This research enhances the current design knowledge of submerged inlets through the utilisation of data mining and Computational Fluid Dynamics (CFD) methodologies, focusing on design space optimisation. A two-pronged approach is employed where the first step encompasses a low-fidelity model through data mining and surrogate modelling to predict and optimise the design parameters, while the second step uses the Design of Experiments (DOE) approach based on the CFD results for the candidate design geometry to construct a surrogate model with high fidelity for design refinement. The feasibility of the proposed methodology is demonstrated for the optimisation of the total pressure recovery of a NACA submerged inlet for the subsonic flight regime. The proposed methodology is found to provide good agreement between the surrogate and CFD-based model and reduce the optimisation processing time by half in comparison with conventional (global-based) CFD optimisation approaches.

Frequency optimization of laminated functionally graded carbon nanotube reinforced composite quadrilateral plates using smoothed FEM and evolution algorithm

2017 ◽  
Vol 52 (14) ◽  
pp. 1971-1986 ◽  
Author(s):  
T Vo-Duy ◽  
T Truong-Thi ◽  
V Ho-Huu ◽  
T Nguyen-Thoi
Keyword(s):  
Carbon Nanotube ◽  
Optimization Problem ◽  
Volume Fraction ◽  
Differential Evolution Algorithm ◽  
Composite Plates ◽  
Functionally Graded ◽  
Optimization Approach ◽  
Reinforced Composite ◽  
Design Variables ◽  
Evolution Algorithm

The paper presents an efficient numerical optimization approach to deal with the optimization problem for maximizing the fundamental frequency of laminated functionally graded carbon nanotube-reinforced composite quadrilateral plates. The proposed approach is a combination of the cell-based smoothed discrete shear gap method (CS-DSG3) for analyzing the first natural frequency of the functionally graded carbon nanotube reinforced composite plates and a global optimization algorithm, namely adaptive elitist differential evolution algorithm (aeDE), for solving the optimization problem. The design variables are the carbon nanotube orientation in the layers and constrained in the range of integer numbers belonging to [−900 900]. Several numerical examples are presented to investigate optimum design of quadrilateral laminated functionally graded carbon nanotube reinforced composite plates with various parameters such as carbon nanotube distribution, carbon nanotube volume fraction, boundary condition and number of layers.

Modeling and control of a quadrotor tail-sitter unmanned aerial vehicles

2021 ◽  
pp. 095965182110504
Author(s):  
Hongbo Xin ◽  
Yujie Wang ◽  
Xianzhong Gao ◽  
Qingyang Chen ◽  
Bingjie Zhu ◽  
...  
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Euler Angle ◽  
Level Flight ◽  
Aerial Vehicles ◽  
Flight Mode ◽  
Aerial Vehicle ◽  
Hover Flight ◽  
And Control

The tail-sitter unmanned aerial vehicles have the advantages of multi-rotors and fixed-wing aircrafts, such as vertical takeoff and landing, long endurance and high-speed cruise. These make the tail-sitter unmanned aerial vehicle capable for special tasks in complex environments. In this article, we present the modeling and the control system design for a quadrotor tail-sitter unmanned aerial vehicle whose main structure consists of a traditional quadrotor with four wings fixed on the four rotor arms. The key point of the control system is the transition process between hover flight mode and level flight mode. However, the normal Euler angle representation cannot tackle both of the hover and level flight modes because of the singularity when pitch angle tends to [Formula: see text]. The dual-Euler method using two Euler-angle representations in two body-fixed coordinate frames is presented to couple with this problem, which gives continuous attitude representation throughout the whole flight envelope. The control system is divided into hover and level controllers to adapt to the two different flight modes. The nonlinear dynamic inverse method is employed to realize fuselage rotation and attitude stabilization. In guidance control, the vector field method is used in level flight guidance logic, and the quadrotor guidance method is used in hover flight mode. The framework of the whole system is established by MATLAB and Simulink, and the effectiveness of the guidance and control algorithms are verified by simulation. Finally, the flight test of the prototype shows the feasibility of the whole system.

Qualitative Knowledge and Manufacturing Considerations in Multidisciplinary Structural Optimization of Hybrid Material Structures

2006 ◽  
Vol 10 ◽  
pp. 143-152 ◽  
Author(s):  
Martin Huber ◽  
Horst Baier
Keyword(s):  
Hybrid Material ◽  
Optimization Problem ◽  
Fuzzy Rule ◽  
Optimal Designs ◽  
Design Parameters ◽  
Optimization Approach ◽  
Structural Level ◽  
Design Problems ◽  
Qualitative Knowledge ◽  
Typical Design

An optimization approach is derived from typical design problems of hybrid material structures, which provides the engineer with optimal designs. Complex geometries, different materials and manufacturing aspects are handled as design parameters using a genetic algorithm. To take qualitative information into account, fuzzy rule based systems are utilized in order to consider all relevant aspects in the optimization problem. This paper shows results for optimization tasks on component and structural level.

scholarly journals Design and Optimization for UAV-Enabled Two-Way Relaying System with SWIPT

2020 ◽  
Author(s):  
Jinlong Wang ◽  
Gang Wang ◽  
Guanyi Chen ◽  
Bo Li ◽  
Ruofei Zhou ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Signal To Noise Ratio ◽  
Power Splitting ◽  
Generalized Singular Value Decomposition ◽  
Ratio Requirement ◽  
Design And Optimization ◽  
Aerial Vehicle ◽  
Resource Allocation Scheme ◽  
Value Decomposition ◽  
Relaying System

Abstract In this paper, we investigate the resource allocation scheme for an unmanned-aerial-vehicle-enable (UAV-enabled) two-way relaying system with simultaneous wireless information and power transfer (SWIPT), where two userequipment exchange information with the help of UAV relay and harvest energythrough power splitting (PS) scheme. Under the transmission power constraintsat UEs and UAV relay, a non-convex intractable optimization problem isformulated which maximizes the sum retained energy of two UEs while satisfying the minimum signal-to-noise ratio requirement. We decouple the complicated beamforming and PS factors optimization problem into three solvable subproblems and propose an efficient alternating optimization scheme. Subsequently, in order to reduce the complexity, a robust scheme based on generalized singular value decomposition (GSVD) is designed. Finally, numerical results verify the robustness and effectiveness of two proposed schemes.

Proactive Optimization of Intelligent-Well Production Using Stochastic Gradient-Based Algorithms

2016 ◽  
Vol 19 (02) ◽  
pp. 239-252 ◽  
Author(s):  
Morteza Haghighat Sefat ◽  
Khafiz M. Muradov ◽  
Ahmed H. Elsheikh ◽  
David R. Davies
Keyword(s):  
Large Scale ◽  
Optimization Problem ◽  
Stochastic Gradient ◽  
Real Field ◽  
Directional Derivatives ◽  
Optimization Approach ◽  
Layer By Layer ◽  
Monitoring And Control ◽  
Ensemble Size ◽  
Local Optima

Summary The popularity of intelligent wells (I-wells), which provide layer-by-layer monitoring and control capability of production and injection, is growing. However, the number of available techniques for optimal control of I-wells is limited (Sarma et al. 2006; Alghareeb et al. 2009; Almeida et al. 2010; Grebenkin and Davies 2012). Currently, most of the I-wells that are equipped with interval control valves (ICVs) are operated to enhance the current production and to resolve problems associated with breakthrough of the unfavorable phase. This reactive strategy is unlikely to deliver the long-term optimum production. On the other side, the proactive-control strategy of I-wells, with its ambition to provide the optimum control for the entire well's production life, has the potential to maximize the cumulative oil production. This strategy, however, results in a high-dimensional, nonlinear, and constrained optimization problem. This study provides guidelines on selecting a suitable proactive optimization approach, by use of state-of-the-art stochastic gradient-approximation algorithms. A suitable optimization approach increases the practicality of proactive optimization for real field models under uncertain operational and subsurface conditions. We evaluate the simultaneous-perturbation stochastic approximation (SPSA) method (Spall 1992) and the ensemble-based optimization (EnOpt) method (Chen et al. 2009). In addition, we present a new derivation of the EnOpt by use of the concept of directional derivatives. The numerical results show that both SPSA and EnOpt methods can provide a fast solution to a large-scale and multiple I-well proactive optimization problem. A criterion for tuning the algorithms is proposed and the performance of both methods is compared for several test cases. The used methodology for estimating the gradient is shown to affect the application area of each algorithm. SPSA provides a rough estimate of the gradient and performs better in search environments, characterized by several local optima, especially with a large ensemble size. EnOpt was found to provide a smoother estimation of the gradient, resulting in a more-robust algorithm to the choice of the tuning parameters, and a better performance with a small ensemble size. Moreover, the final optimum operation obtained by EnOpt is smoother. Finally, the obtained criteria are used to perform proactive optimization of ICVs in a real field.

Optimisation Studies for an Efficient Aerodynamic Configuration of a Blended Wing Unmanned Aerial Vehicle

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
M.K. Padmanabhan ◽  
G. Santhoshkumar ◽  
Praveen Narayan ◽  
N. Jeevaraj ◽  
M. Dinesh ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Focal Point ◽  
Lift Coefficient ◽  
Innovative Design ◽  
Aerodynamic Efficiency ◽  
Payload Capacity ◽  
Aerial Vehicle ◽  
Computational Fluid Dynamics Cfd ◽  
The Cost ◽  
Long Endurance

There are various configurations and parameters that contribute to the Design of Unmanned Aerial Vehicles for specific applications. This paper deals with an innovative design of an unmanned aerial vehicle for a specified class of UAVs that require demands such as long endurance, minimized landing space with vertical take-off and landing (VTOL) capabilities. The focal point of this design is superimposing the high endurance blended wing design into tri-copter to address these parameters. The preliminary calculations are initially performed for the blended wing VTOL vehicle based on the required payload capacity and endurance. Superimposing the tri-copter will decrease the aerodynamic efficiency of the vehicle. Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical methods and algorithms to solve complex problems involving fluid flow which will effectively employed to reduce the cost and time during the conceptual and preliminary design stages. CFD analysis was carried out to estimate the major parameters like lift, drag, lift coefficient (CL) and drag coefficient (CD) for various Angle of Attack (AoA) for configurations of blended wing vehicle with and without tri-copter system in the cruise condition. Thus, the vehicle design and propulsion system is effectively optimized using this drag estimation.

Impact-Resistant Flying Platform for Use in the Urban Construction Monitoring

2021 ◽  
pp. 520-551
Author(s):  
Konstantin Dergachov ◽  
Anatolii Kulik
Keyword(s):  
Spatial Dynamics ◽  
Construction Monitoring ◽  
Model Based Control ◽  
Video Cameras ◽  
Urban Construction ◽  
Flight Mode ◽  
Aerial Vehicle ◽  
Coaxial Rotors ◽  
Advanced Model

A case study drone that constitutes a shock-resistant aerial vehicle is discussed in the chapter. The aerial motor platform is placed in gimbal joints of the exclusive framework (shell). The platform is a helicopter type aerial vehicle powered with two coaxial rotors of contra rotation. Mathematical model of the platform spatial dynamics bases Lagrange's equations to bring reliable solutions so that advanced model-based control law design techniques can be used. Though the case study implies utilizing an automatic flight mode of the aerial vehicle, it can be piloted remotely on radio. The on-board video cameras and other sensors are used to bring about both navigational duties and surveillance missions such as building constructions monitoring.

scholarly journals On the Sensitivity of Local Flexibility Markets to Forecast Error: A Bi-Level Optimization Approach

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1959
Author(s):  
Delaram Azari ◽  
Shahab Shariat Torbaghan ◽  
Hans Cappon ◽  
Karel J. Keesman ◽  
Madeleine Gibescu ◽  
...  
Keyword(s):  
Distribution System ◽  
Large Scale ◽  
Optimization Problem ◽  
Distribution Networks ◽  
Second Order ◽  
Optimization Approach ◽  
Second Order Cone ◽  
Local Flexibility ◽  
Level Problem ◽  
Relaxation Error

The large-scale integration of intermittent distributed energy resources has led to increased uncertainty in the planning and operation of distribution networks. The optimal flexibility dispatch is a recently introduced, power flow-based method that a distribution system operator can use to effectively determine the amount of flexibility it needs to procure from the controllable resources available on the demand side. However, the drawback of this method is that the optimal flexibility dispatch is inexact due to the relaxation error inherent in the second-order cone formulation. In this paper we propose a novel bi-level optimization problem, where the upper level problem seeks to minimize the relaxation error and the lower level solves the earlier introduced convex second-order cone optimal flexibility dispatch (SOC-OFD) problem. To make the problem tractable, we introduce an innovative reformulation to recast the bi-level problem as a non-linear, single level optimization problem which results in no loss of accuracy. We subsequently investigate the sensitivity of the optimal flexibility schedules and the locational flexibility prices with respect to uncertainty in load forecast and flexibility ranges of the demand response providers which are input parameters to the problem. The sensitivity analysis is performed based on the perturbed Karush–Kuhn–Tucker (KKT) conditions. We investigate the feasibility and scalability of the proposed method in three case studies of standardized 9-bus, 30-bus, and 300-bus test systems. Simulation results in terms of local flexibility prices are interpreted in economic terms and show the effectiveness of the proposed approach.

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