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Rheological model optimization using advanced evolutionary computation for the analysis of the influence of recycled rubber on rubber blend dynamical behaviour

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MECCANICA 2013年第10期48卷 2467-2477页

作者： Pavlovic, Ivan Ciric, Ivan Djekic, Petar Nikolic, Vlastimir Pavlovic, Ratko Cojbasic, Zarko Radenkovic, Goran Univ Nis Fac Mech Engn Aleksandra Medvedeva 14 Nish 18000 Serbia

Rheological models of tested rubber blend samples, with different ratios of smut/recycled material, were developed, analyzed and discussed according to experimental data. The experimental measurements show the dynamical behavior of these samples after a short-term axial load. The rheological model of samples was assumed as a viscoelastic Voigt-Maxwell and hyperelastic Mooney-Rivlin model. real coded genetic algorithms were implemented for optimal model parameters identification in order to minimize the difference between the real sample behavior and dynamical model output. Numerical results obtained for analyzed mixture were compared with the original sample to verify the presented method. In purpose of predicting the dynamical characteristics for desirable rubber blends, an interrelation was formed based on the concentration of recycled material in sample blends and dynamical model parameters dependence.

关键词： Rheological model real coded genetic algorithm Rubber blends Dynamical characteristics

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real coded GA optimized fuzzy logic controlled PEMFC based Dynamic Voltage Restorer for reparation of voltage disturbances in distribution system

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2017年第1期42卷 603-613页

作者： Sundarabalan, C. K. Selvi, K. PR Engn Coll Dept Elect & Elect Engn Thanjavur 613403 Tamil Nadu India Thiagarajar Coll Engn Dept Elect & Elect Engn Madurai 625015 Tamil Nadu India

A voltage disturbance is one of the major power quality problems in electric power distribution system. Dynamic Voltage Restorer (DVR) is the effective device for compensation of voltage based power quality problems in distribution system. In this paper, the DVR is modelled to protect sensitive load from source side voltage disturbances under nonlinear load conditions. The real coded genetic algorithm (GA) optimized fuzzy logic controller is used to control both d and q components of the voltage. In addition to the compensation of harmonics in the load voltage, the proposed system is able to compensate both balanced and unbalanced voltage sag/swell in the load side. The effectiveness of the proposed DVR system under different types of fault condition is analyzed in MATLAB platform. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Dynamic Voltage Restorer (DVR) real coded genetic algorithm Power quality Fuzzy logic

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Application of RCGA-ANN approach for modeling kerf width and surface roughness in CO₂ laser cutting of mild steel

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JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING 2013年第2期35卷 103-110页

作者： Madic, Milos Radovanovic, Miroslav Univ Nis Fac Mech Engn Nish 18000 Serbia

This paper presents an artificial intelligence approach for the development of predictive models for a CO2 laser cutting of mild steel by using artificial neural networks (ANNs) and real coded genetic algorithm (RCGA). Laser cutting experiment, conducted according to Taguchi's experimental design using L (25) orthogonal array, provided a set of data for the development of ANN models for the prediction of the kerf width and surface roughness. Both ANN models considered cutting speed, laser power, and assist gas pressure as input parameters. Considering the disadvantages of the back propagation, the RCGA was applied for training of the ANNs. Statistical results indicate good correlation between the experimental results and ANN predictions, which confirms the validity of the applied approach. Finally, using the developed models, the combined effects of input process parameters on the quality characteristics were studied.

关键词： Carbon dioxide (CO2) laser cutting Artificial neural networks Modeling Kerf width Surface roughness real coded genetic algorithm

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real time Implementation of SHE PWM in Single Phase Matrix Converter using Linearization Method

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2015年第4期10卷 1682-1691页

作者： Karuvelam, P. Subha Rajaram, M. Govt Coll Engn Dept Elect & Elect Engn Tirunelveli Tamil Nadu India Anna Univ Dept Elect & Elect Engn Madras 600025 Tamil Nadu India

In this paper, a real time implementation of selective harmonic elimination pulse width modulation (SHEPWM) using real coded genetic algorithm (RGA), Particle Swarm Optimization technique (PSO) and a new technique known as Linearization Method (LM) for Single Phase Matrix Converter (SPMC) is designed and discussed. In the proposed technique, the switching frequency is fixed and the optimum switching angles are obtained using simple mathematical calculations. A MATLAB simulation was carried out, and FFT analysis of the simulated output voltage waveform confirms the effectiveness of the proposed method. An experimental setup was also developed, and the switching angles and firing pulses are generated using Field Programmable Gate Array (FPGA) processor. The proposed method proves that it is much applicable in the industrial applications by virtue of its suitability in real time applications.

关键词： Single Phase matrix converter Selective harmonic elimination pulse width modulation real coded genetic algorithm Particle swarm optimization Total harmonic distortion

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Design optimization of spur gear using SA and RCGA

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JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING 2018年第5期40卷 1-8页

作者： Rai, Paridhi Barman, Asim Gopal Natl Inst Technol Patna Dept Mech Engn Patna Bihar India

Gear size is one of the most important criteria in design optimization of gear set used in automotive, aeronautical and various other applications. Smaller gear size results in requirement of less material and hence reducing manufacturing cost. This paper aims at minimizing center distance of spur gear set to obtain its corresponding optimal design variables. Design variables included in this study are diametrical pitch and number of pinion teeth. real coded genetic algorithm and simulated annealing are employed for performing design optimization procedure. In this study, along with constraints on bending strength, contact strength, interference and contact ratio, scoring has been added as design constraint in design problem. All the design factors included in design procedure are considered as per AGMA standards. The recommended optimization techniques are implemented on a design example and optimum values of design variables are obtained. The obtained results are compared with those obtained by traditional design procedure to find the better solution as well as better optimization technique. Variations in input power and gear ratio have been done to verify their effect on the objective function and to further investigate a more useful optimization technique for gear design.

关键词： Spur gear Centre distance minimization real coded genetic algorithm Simulated annealing

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Radiation Pattern Optimization for Concentric Circular Antenna Array With Central Element Feeding Using Craziness-Based Particle Swarm Optimization

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2010年第5期20卷 577-586页

作者： Mandal, Durbadal Ghoshal, Sakti Prasad Bhattacharjee, Anup Kumar Natl Inst Technol Dept Elect & Commun Engn Durgapur 713209 W Bengal India Natl Inst Technol Dept Elect Engn Durgapur 713209 W Bengal India

In this article, two optimization heuristic search techniques, craziness-based particle swarm optimization (CRPSO) and CRPSO with wavelet mutation (CRPSOWM), are applied to the process of optimal designing three-ring concentric circular antenna arrays (CCAAs) focused on maximum sidelobe level (SLL) reduction. Hence, three-ring CCAA without and with central element feeding are considered. SLL is a critical radiation pattern parameter in the task of reducing background noise and interference in the most recent wireless communication systems. To improve the radiation pattern with maximum SLL reduction, an optimum set of antenna element parameters as excitation weights and radii of the rings is to be developed. This is an optimization problem dealing with complex, highly nonlinear, discontinuous, and nondifferentiable array factors of CCAA design. So, one evolutionary optimization technique as CRPSO is adopted. To enhance the optimization performance of CRPSO further in exploring the solution space more effectively for a better solution, the wavelet theory is again applied in terms of mutation. This wavelet mutationbased CRPSO is named as CRPSOWM. It is shown that the proposed CRPSOWM technique outperforms the CRPSO significantly in terms of convergence speed, solution quality, and solution robustness. Computational results finally reveal that among the various CCAA designs, the design containing central element and four, six, and eight elements in three successive concentric rings proves to be the near global optimal design with near global minimum SLL (-43.4 dB) as determined by CRPSOWM. real coded genetic algorithm (RGA) and its wavelet-based improved version (RGAWM) as well are also adopted to compare the results of above particle swarm optimization based algorithms. (C) 2010 Wiley Periodicals. Inc Int J RF and Miciowave CAE 20.577-586. 2010

关键词： concentric circular antenna array sidelobe level particle swarm optimization wavelet mutation real coded genetic algorithm

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Performance Comparison of Differential Evolution, Particle Swarm Optimization and genetic algorithm in the Design of Circularly Polarized Microstrip Antennas

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2014年第8期62卷 3920-3928页

作者： Deb, Arindam Roy, Jibendu Sekhar Gupta, Bhaskar KIIT Univ Sch Elect Engn Bhubaneswar 751024 Orissa India Jadavpur Univ Dept Elect & Telecommun Engn Kolkata 700032 India

Performance evaluation of evolutionary optimization techniques is done with respect to the design of circularly polarized microstrip antennas. The optimization techniques include conventional differential evolution, particle swarm optimization and genetic algorithm along with their advanced schemes. The optimization is done for impedance matching over a predefined frequency range, circular polarization, and high gain at a center frequency. The control parameters of all the algorithms are tuned using meta-level particle swarm optimization algorithm. Three cases are considered with three conventional feeding techniques, namely probe feed, transmission line feed, and the cross-aperture coupled feed. A fuzzified cost function is developed for optimization to ensure proper outcome from each optimization algorithm. The antenna parameters obtained from the algorithm producing best results are fabricated and their performances measured.

关键词： Differential evolution Mamdani fuzzy inference scheme particle swarm optimization real coded genetic algorithm

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A hybrid probabilistic fuzzy goal programming approach for agricultural decision-making

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2016年 173卷 134-141页

作者： Jana, R. K. Sharma, Dinesh K. Chakraborty, B. Indian Inst Social Welf & Business Management Kolkata India Univ Maryland Eastern Shore Princess Anne MD USA Inst Engn & Management Kolkata India

In this paper, we present a probabilistic fuzzy goal programming model to capture different uncertainties in an agricultural decision-making environment. First, we construct the goals of the model as probabilistic fuzzy goals. Next, we convert the probabilistic fuzzy goal programming problem to a probabilistic constrained programming problem. While a deterministic solution to this problem cannot be derived, we use a hybrid approach comprising Monte-Carlo simulation and a real-coded genetic algorithm. The application of the proposed model and the solution technique is demonstrated by considering the agricultural planning of the Danton-II community development block of Paschim Medinipur District, West Bengal, India. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Probabilistic programming Probabilistic fuzzy goal programming real coded genetic algorithm Monte-Carlo simulation Agricultural planning

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Switching model analysis and implementation of electric spring for voltage regulation in smart grids

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第15期11卷 3703-3712页

作者： Areed, Emad Fuad Abido, Mohammad A. Al-Awami, Ali T. King Fahd Univ Petr & Minerals Dept Elect Engn Dhahran 31261 Saudi Arabia

This study proposes a new switching model for steady-state and dynamic analysis of an electric spring (ES). The accuracy of the developed ES model is demonstrated. The developed model is used to design a controller for bus voltage regulation in a distribution network with an intermittent renewable source. The ES controller design problem is formulated as an optimisation problem with a time domain-based objective function to reduce the time-weighted voltage deviations. real coded genetic algorithm is considered for optimal design of the AC and DC PI controllers of the ES. The distribution system with ES is simulated and the developed model is investigated under different types of disturbances and load variations. In addition, the system considered is developed on real time digital simulator and the proposed controllers are implemented on dSPACE DS1103 platform for a hardware-in-loop experimental setup. Simulation results have been validated by the experimental results. The results show the effectiveness of the developed model and the proposed controller design approach to enhance greatly the reliability of the distribution network considered.

关键词： power distribution reliability voltage control switching systems (control) control system synthesis time-domain analysis genetic algorithms renewable energy sources PI control smart power grids power distribution control switching model analysis electric spring smart grids ES model bus voltage regulation distribution network reliability controller design approach time domain-based objective function optimisation problem time-weighted voltage deviations AC controllers DC controllers PI controllers distribution system disturbances load variations real time digital simulator dSPACE DS1103 platform hardware-in-loop experimental setup real coded genetic algorithm intermittent renewable source

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Economic environmental dispatch of fixed head hydrothermal power systems using nondominated sorting genetic algorithm-II

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APPLIED SOFT COMPUTING 2011年第3期11卷 3046-3055页

作者： Basu, M. Jadavpur Univ Dept Power Engn Kolkata 700098 W Bengal India

This paper presents nondominated sorting genetic algorithm-II for economic environmental dispatch of fixed head hydrothermal power systems. The problem is formulated as a nonlinear constrained multi-objective optimization problem. Nondominated sorting genetic algorithm-II is proposed to handle economic environmental dispatch of fixed head hydrothermal power systems as a true multiobjective optimization problem with competing and noncommensurable objectives. Numerical results of two test systems demonstrate the capabilities of the proposed approach. Results obtained from the proposed approach have been compared with those obtained from strength pareto evolutionary algorithm 2, multiobjective differential evolution and previously obtained results. (C) 2010 Elsevier B. V. All rights reserved.

关键词： Hydrothermal system Multi-objective optimization Nondominated sorting genetic algorithm-II real coded genetic algorithm

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