scholarly journals An Optimization Problem for Quadcopter Reference Flight Trajectory Generation

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Karam Eliker ◽  
Guoqing Zhang ◽  
Said Grouni ◽  
Weidong Zhang
Keyword(s):  
Minimum Energy ◽  
Trajectory Generation ◽  
Optimization Method ◽  
Performance Criteria ◽  
Spline Functions ◽  
Flight Trajectory ◽  
B Spline ◽  
Aerial Vehicle ◽  
And Performance ◽  
Minimum Energy Cost

This paper deals with the reference flight trajectory generation and planning problems for quadcopter Unmanned Aerial Vehicle (UAV). The reference flight trajectory is defined as the composition of path and motion functions. Both of them are generated by using quintic B-spline functions. Based on differential flatness approach, the quadcopter dynamical constraints are satisfied instantaneously by computing the induced aerodynamical moments and lift force. The optimal reference flight trajectory, with respect to the mission requirements and imposed constraints, is reached by manipulating the control points’ vectors of B-spline functions via a nonlinear constrained optimization method. The mission requirements are defined as a set of waypoints with their respective scheduled flight timetable. A minimum-energy cost function is developed to minimize the consumed energy and induced efforts by reference flight trajectory. For the need of the optimal overfly-times schedule, the overfly times with respect to the defined constraints and performance criteria are calculated. Numerical simulation results show the feasibility and effectiveness of the proposed optimization method.

Unmanned aerial vehicle derivative design optimization based on light sport aircraft

2016 ◽  
Vol 231 (3) ◽  
pp. 485-496 ◽  
Author(s):  
Hyeong-Uk Park ◽  
Joon Chung ◽  
Jae-Woo Lee ◽  
Daniel Neufeld
Keyword(s):  
Design Optimization ◽  
Unmanned Aerial Vehicle ◽  
Design Process ◽  
Optimization Technique ◽  
Optimization Method ◽  
Vehicle Design ◽  
Baseline Design ◽  
Aerial Vehicle ◽  
Design Requirements ◽  
And Performance

Manufacturers often develop new products by modifying and extending existing products in order to achieve new market demands while minimizing development time and manufacturing costs. In this research, an efficient derivative design process was developed to efficiently adapt existing aircraft designs according to new requirements. The proposed design process was evaluated using a case study that derives an unmanned aerial vehicle design from a baseline manned 2-seatlight sport aircraft. Multiple unmanned aerial vehicle operational scenarios were analysed to define the requirements of the derivative aircraft. These included patrol, environmental monitoring, and communications relay missions. Each mission has different requirements and therefore each resulting derivative unmanned aerial vehicle design has different geometry, devices, and performance. The derivative design process involved redefining the design requirements and identifying the minimum design variable set that needed to be considered in order to efficiently adapt the baseline design. Uncertainty was considered as well to enhance the reliability of the optimized result when it considered different conditions for each mission. An optimization method based on the possibility based design optimization was proposed to handle uncertainty that arises in the design requirements for the multi-role nature of unmanned aerial vehicles. In this paper, the possibility based design optimization method was implemented with multidisciplinary design optimization technique to derive the derivative unmanned designs based on originally manned aircraft. This approach prevented constraint violation via uncertainty variations in the operating altitude and payload weight for each. The unmanned aerial vehicle derivative designs satisfying the requirements of three different missions were derived from the proposed design process.

scholarly journals Minimum-Energy Multiwavelet Frames with Arbitrary Integer Dilation Factor

2012 ◽  
Vol 2012 ◽  
pp. 1-37 ◽  
Author(s):  
Yongdong Huang ◽  
Qiufu Li ◽  
Ming Li
Keyword(s):  
Necessary Conditions ◽  
Minimum Energy ◽  
Sufficient Conditions ◽  
Spline Functions ◽  
Arbitrary Integer ◽  
B Spline ◽  
Numerical Examples ◽  
Dilation Factor ◽  
Organically Combine

In order to organically combine the minimum-energy frame with the significant properties of multiwavelets, minimum-energy multiwavelet frames with arbitrary integer dilation factor are studied. Firstly, we define the concept of minimum-energy multiwavelet frame with arbitrary dilation factor and present its equivalent characterizations. Secondly, some necessary conditions and sufficient conditions for minimum-energy multiwavelet frame are given. Thirdly, the decomposition and reconstruction formulas of minimum-energy multiwavelet frame with arbitrary integer dilation factor are deduced. Finally, we give several numerical examples based on B-spline functions.

Dimensioning a recovery boiler furnace using mathematical optimization

TAPPI Journal ◽  
2015 ◽  
Vol 14 (2) ◽  
pp. 119-129 ◽  
Author(s):  
VILJAMI MAAKALA ◽  
PASI MIIKKULAINEN
Keyword(s):  
Radial Basis Function Network ◽  
High Capacity ◽  
Mathematical Optimization ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Performance Criteria ◽  
Boiler Furnace ◽  
Starting Point ◽  
Recovery Boiler ◽  
Base Design

Capacities of the largest new recovery boilers are steadily rising, and there is every reason to expect this trend to continue. However, the furnace designs for these large boilers have not been optimized and, in general, are based on semiheuristic rules and experience with smaller boilers. We present a multiobjective optimization code suitable for diverse optimization tasks and use it to dimension a high-capacity recovery boiler furnace. The objective was to find the furnace dimensions (width, depth, and height) that optimize eight performance criteria while satisfying additional inequality constraints. The optimization procedure was carried out in a fully automatic manner by means of the code, which is based on a genetic algorithm optimization method and a radial basis function network surrogate model. The code was coupled with a recovery boiler furnace computational fluid dynamics model that was used to obtain performance information on the individual furnace designs considered. The optimization code found numerous furnace geometries that deliver better performance than the base design, which was taken as a starting point. We propose one of these as a better design for the high-capacity recovery boiler. In particular, the proposed design reduces the number of liquor particles landing on the walls by 37%, the average carbon monoxide (CO) content at nose level by 81%, and the regions of high CO content at nose level by 78% from the values obtained with the base design. We show that optimizing the furnace design can significantly improve recovery boiler performance.

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