scholarly journals Metaheuristic Regression Equations for Split-Ring Resonator Using Time-Varying Particle Swarm Optimization Algorithm

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 300
Author(s):  
Muhammad Mughal ◽  
Tahir Ejaz ◽  
Arshad ◽  
Ashiq Hussain
Keyword(s):  
Particle Swarm Optimization ◽  
Resonant Frequency ◽  
Quality Factor ◽  
Ring Resonator ◽  
Particle Swarm ◽  
Split Ring Resonator ◽  
Regression Equations ◽  
Time Varying ◽  
Split Ring ◽  
Swarm Optimization

This article presents a new technique for determining accurate values of resonant frequency and quality factor pertaining to the split-ring resonator. Different conducting shield materials have been used around a copper split-ring. The split-ring has been designed to operate at about 2.1 GHz. Various equations were worked out earlier to determine the values of resonant frequency and quality factor. However, these equations yielded different solutions. Therefore, simulations were used to obtain the values of the resonant frequency and quality factor of the split-ring resonator with different five-shield materials, using High-Frequency Structure Simulator (HFSS) software. In this work, a novel method has been introduced for obtaining values of resonant frequency which provides results with negligible error. An optimal technique, namely time-varying particle swarm optimization (TVPSO), was then performed to obtain two sets of equations for resonant frequency and quality factor. The two sets of equations, optimized using TVPSO, were compared for their effectiveness in matching the actual frequency and quality factor for each of the five materials. It was found that the TVPSO was significant in achieving the frequency and quality factor regression equation to accurately resemble the actual values portrayed by the low mean absolute error.

scholarly journals Shield Optimization and Formulation of Regression Equations for Split-Ring Resonator

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Tahir Ejaz ◽  
Hamood Ur Rahman ◽  
T. Tauqeer ◽  
Adnan Masood ◽  
Tahir Zaidi
Keyword(s):  
Resonant Frequency ◽  
Quality Factor ◽  
Ring Resonator ◽  
Low Cost ◽  
Split Ring Resonator ◽  
Ring Resonators ◽  
Regression Equations ◽  
Split Ring ◽  
Optimum Result ◽  
5 Ghz

Microwave resonators are widely used for numerous applications including communication, biomedical and chemical applications, material testing, and food grading. Split-ring resonators in both planar and nonplanar forms are a simple structure which has been in use for several decades. This type of resonator is characterized with low cost, ease of fabrication, moderate quality factor, low external noise interference, high stability, and so forth. Due to these attractive features and ease in handling, nonplanar form of structure has been utilized for material characterization in 1–5 GHz range. Resonant frequency and quality factor are two important parameters for determination of material properties utilizing perturbation theory. Shield made of conducting material is utilized to enclose split-ring resonator which enhances quality factor. This work presents a novel technique to develop shield around a predesigned nonplanar split-ring resonator to yield optimized quality factor. Based on this technique and statistical analysis regression equations have also been formulated for resonant frequency and quality factor which is a major outcome of this work. These equations quantify dependence of output parameters on various factors of shield made of different materials. Such analysis is instrumental in development of devices/designs where improved/optimum result is required.

scholarly journals Complex Permittivity Characterization of Liquid Samples Based on a Split Ring Resonator (SRR)

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3385
Author(s):  
Jialu Ma ◽  
Jingchao Tang ◽  
Kaicheng Wang ◽  
Lianghao Guo ◽  
Yubin Gong ◽  
...  
Keyword(s):  
Resonant Frequency ◽  
Complex Permittivity ◽  
Ring Resonator ◽  
High Sensitivity ◽  
Split Ring Resonator ◽  
Debye Model ◽  
Split Ring ◽  
Liquid Samples ◽  
Microwave Sensor

A complex permittivity characterization method for liquid samples has been proposed. The measurement is carried out based on a self-designed microwave sensor with a split ring resonator (SRR), the unload resonant frequency of which is 5.05 GHz. The liquid samples in capillary are placed in the resonant zone of the fabricated senor for high sensitivity measurement. The frequency shift of 58.7 MHz is achieved when the capillary is filled with ethanol, corresponding a sensitivity of 97.46 MHz/μL. The complex permittivity of methanol, ethanol, isopropanol (IPA) and deionized water at the resonant frequency are measured and calibrated by the first order Debye model. Then, the complex permittivity of different concentrations of aqueous solutions of these materials are measured by using the calibrated sensor system. The results show that the proposed sensor has high sensitivity and accuracy in measuring the complex permittivity of liquid samples with volumes as small as 0.13 μL. It provides a useful reference for the complex permittivity characterization of small amount of liquid chemical samples. In addition, the characterization of an important biological sample (inositol) is carried out by using the proposed sensor.

Inverse estimation of time-varying heat transfer coefficients for a hollow cylinder by using self-learning particle swarm optimization

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Kun-Yung Chen ◽  
Te-Wen Tu
Keyword(s):  
Heat Transfer ◽  
Particle Swarm Optimization ◽  
Objective Function ◽  
Hollow Cylinder ◽  
General Type ◽  
Particle Swarm ◽  
Time History ◽  
Time Varying ◽  
Swarm Optimization ◽  
Self Learning

Abstract An inverse methodology is proposed to estimate a time-varying heat transfer coefficient (HTC) for a hollow cylinder with time-dependent boundary conditions of different kinds on inner and outer surfaces. The temperatures at both the inner surface and the interior domain are measured for the hollow cylinder, while the time history of HTC of the outer surface will be inversely determined. This work first expressed the unknown function of HTC in a general form with unknown coefficients, and then regarded these unknown coefficients as the estimated parameters which can be randomly searched and found by the self-learning particle swarm optimization (SLPSO) method. The objective function which wants to be minimized was found with the absolute errors between the measured and estimated temperatures at several measurement times. If the objective function converges toward the null, the inverse solution of the estimated HTC will be found eventually. From numerical experiments, when the function of HTC with exponential type is performed, the unknown coefficients of the HTC function can be accurately estimated. On the contrary, when the function of HTC with a general type is conducted, the unknown coefficients of HTC are poorly estimated. However, the estimated coefficients of an HTC function with the general type can be regarded as the equivalent coefficients for the real function of HTC.

scholarly journals Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yong Ma ◽  
M. Zamirian ◽  
Yadong Yang ◽  
Yanmin Xu ◽  
Jing Zhang
Keyword(s):  
Particle Swarm Optimization ◽  
Penalty Function ◽  
Particle Swarm ◽  
Goal Function ◽  
Optimization Method ◽  
Mobile Object ◽  
Time Varying ◽  
Swarm Optimization ◽  
Calculus Of Variation ◽  
Mobile Objects

We present one algorithm based on particle swarm optimization (PSO) with penalty function to determine the conflict-free path for mobile objects in four-dimension (three spatial and one-time dimensions) with obstacles. The shortest path of the mobile object is set as goal function, which is constrained by conflict-free criterion, path smoothness, and velocity and acceleration requirements. This problem is formulated as a calculus of variation problem (CVP). With parametrization method, the CVP is converted to a time-varying nonlinear programming problem (TNLPP). Constraints of TNLPP are transformed to general TNLPP without any constraints through penalty functions. Then, by using a little calculations and applying the algorithm PSO, the solution of the CVP is consequently obtained. Approach efficiency is confirmed by numerical examples.

scholarly journals Path Planning for Unmanned Underwater Vehicle Based on Improved Particle Swarm Optimization Method

2018 ◽  
Vol 14 (12) ◽  
pp. 137
Author(s):  
Jianhua Xu ◽  
Hao Gu ◽  
Hongtao Liang
Keyword(s):  
Particle Swarm Optimization ◽  
Path Planning ◽  
Potential Field ◽  
Particle Swarm ◽  
Underwater Vehicle ◽  
Time Varying ◽  
Slowly Varying Function ◽  
Swarm Optimization ◽  
Improved Particle Swarm Optimization ◽  
Unmanned Underwater Vehicle

Path planning of Unmanned Underwater Vehicle (UUV) is of considerable significance for the underwater navigation, the objective of the path planning is to find an optimal collision-free and the shortest trajectory from the start to the destination. In this paper, a new improved particle swarm optimization (IPSO) was proposed to process the global path planning in a static underwater environment for UUV. Firstly, the path planning principle for UUV was established, in which three cost functions, path length, exclusion potential field between the UUV and obstacle, and attraction potential field between UUV and destination, were considered and developed as an optimization objective. Then, on the basis of analysis traditional particle swarm optimization (PSO), the time-varying acceleration coefficients and slowly varying function were employed to improve performance of PSO, time-varying acceleration coefficients was utilized to balance the local optimum and global optimum, and slowly varying function was introduced into the updating formula of PSO to expand search space and maintain particle diversity. Finally, numerical simulations verify that, the proposed approach can fulfill path planning problems for UUN successfully.

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