Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

Kok, Kai Yit; Rajendran, Parvathy

doi:10.1371/journal.pone.0150558

Cited by 41 publications

(24 citation statements)

References 40 publications

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“…This is performed by initially depositing randomly the sphere centers ensuring a uniform initial distribution on the surface of each pore cell. The minimization of the overlapping function is performed using the differential evolution algorithm [31].…”

Section: Non-overlapping Packing Of Spheres On a Sphere Surfacementioning

confidence: 99%

“…The effect of pore wall thickness on the foam reconstruction is portrayed in Figure 3a distribution on the surface of each pore cell. The minimization of the overlapping function is performed using the differential evolution algorithm [31]. However, there is a significant probability that the resulting macro-voids overlap with each other, creating extra spherical caps that would create extra pore windows connecting the macrovoids, a process that must be included in the reconstruction process.…”

Section: Thickness Of the Macrovoidsmentioning

confidence: 99%

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Three-Dimensional Digital Reconstruction of Ti2AlC Ceramic Foams Produced by the Gelcast Method

2019

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A digital reconstruction technique is presented that generates three-dimensional (3D) digital representations of ceramic foams created by the foam-gelcasting technique. The reconstruction process uses information that is directly extracted from Scanning Electron Microscopy (SEM) images and offers a 3D representation of the physical sample accounting for the typically large pore cavities and interconnecting windows that are formed during the preparation process. Contrary to typical tessellation-based foam treatments, a spherical representation of the pores and the pore windows of the foams is assumed and a novel hybrid algorithm that combines a variation of Lubachevsky-type and Random Close Packing of Hard Spheres (RCPHS) algorithms has been developed to obtain near-optimum solutions to the packing problem of the spheres that represent the pores. Numerical simulations are performed directly on the 3D reconstructed foams to determine their gas permeability. The model predictions are compared with experimental gas permeability data that were obtained for the physical samples. The pore wall thickness can be treated as the single fitting parameter in the entire reconstruction process, although it is shown that images of sufficient resolution could eliminate the need even for that. The foams that are produced by this method yield quantitatively similar pressure drops with experiments for various superficial velocity values, with a very small deviation in the range of 1.7–2.8%. The proposed methodology could be utilized for the prediction of the permeability and transport properties of complex foamy porous structures, similar to the gelcast-type of foams, from a single SEM image of the foam sample without resorting to serial tomography or other structural information, thus saving considerable time and effort from experimental work.

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Section: Non-overlapping Packing Of Spheres On a Sphere Surfacementioning

confidence: 99%

Section: Thickness Of the Macrovoidsmentioning

confidence: 99%

Three-Dimensional Digital Reconstruction of Ti2AlC Ceramic Foams Produced by the Gelcast Method

2019

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“…The torque equations that include gyroscopic effects are given in equation (3). c d is the drag coefficient.…”

Section: Mathematical Model Of Quadrocoptermentioning

confidence: 99%

Attitude controller optimization of four-rotor unmanned air vehicle

Erkol

2017

International Journal of Micro Air Vehicles

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Quadrocopters, which are getting much popular day to day, are unmanned air vehicles which have four rotors to fly and maneuver in the air. They are used in military or commercial areas. Researchers are also interested in quadrocopters because their physical structure is simple; they can be modeled linear or nonlinear; and many problems about control, optimization, or artificial intelligence can be studied on it. A stable quadrocopter design requires firstly a good controller design. There are many control methods applied to quadrocopters but the most used one is the PID controller. Every controller needs to be tuned well for a good performance. Optimization algorithms are one of the popular tools for tuning the controllers. They can be used to produce optimum controller parameters with less experiment and in a short time. Each optimization algorithm has a different characteristic and different performance depending on the problem. So a comparison is needed among some popularly used optimization algorithms. In this study, a quadrocopter is modeled, and four PID controllers are designed to control attitude and hover. The optimum parameters for controllers are determined by the artificial bee colony algorithm, particle swarm optimization, and genetic algorithm. Performance of the controllers and optimization algorithms is given comparatively.

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“…DE is becoming more and more popular in engineering applications because it: (1) relies on rather simple concepts and is easy to implement; (2) does not require gradient information; (3) can be utilized in a wide range of problems covering different disciplines. At present, DE is widely used in many research and engineering fields, such as neural network parameter training, pattern synthesis, path planning of Unmanned Aerial Vehicle and other research and engineering fields [2]- [4].…”

Section: Introductionmentioning

confidence: 99%

Hybridizing Dragonfly Algorithm with Differential Evolution for Global Optimization

Duan

Yang

et al. 2019

IEICE Trans. Inf. & Syst.

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Due to its simplicity and efficiency, differential evolution (DE) has gained the interest of researchers from various fields for solving global optimization problems. However, it is prone to premature convergence at local minima. To overcome this drawback, a novel hybrid dragonfly algorithm with differential evolution (Hybrid DA-DE) for solving global optimization problems is proposed. Firstly, a novel mutation operator is introduced based on the dragonfly algorithm (DA). Secondly, the scaling factor (F) is adjusted in a self-adaptive and individual-dependent way without extra parameters. The proposed algorithm combines the exploitation capability of DE and exploration capability of DA to achieve optimal global solutions. The effectiveness of this algorithm is evaluated using 30 classical benchmark functions with sixteen state-of-the-art meta-heuristic algorithms. A series of experimental results show that Hybrid DA-DE outperforms other algorithms significantly. Meanwhile, Hybrid DA-DE has the best adaptability to high-dimensional problems.

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Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

Cited by 41 publications

References 40 publications

Three-Dimensional Digital Reconstruction of Ti2AlC Ceramic Foams Produced by the Gelcast Method

Three-Dimensional Digital Reconstruction of Ti2AlC Ceramic Foams Produced by the Gelcast Method

Attitude controller optimization of four-rotor unmanned air vehicle

Hybridizing Dragonfly Algorithm with Differential Evolution for Global Optimization

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