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3rd IEEE International Conference on Smart Technologies for Power, Energy and Control, STPEC 2023

作者： Kumar, Akshay Prabhu, M.S. Zeno, Aldrich National Sun Yat-sen University Department of Electrical Engineering Kaohsiung City Taiwan Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Electrical and Electronics Engineering India Norwegian University of Science and Technology Department of Electrical Energy Norway

ISBN: (纸本)9798350304732

In this paper, dynamic and steady-state stability enhancement of tidal turbine based direct driven permanent magnet synchronous generator with gate controlled series capacitor (GCSC) is presented. To accomplish this objective, a reserve power margin is created on tidal power generation (TPG) using speed control and pitch angle control strategies to deliver supplementary active power to the system in case of system events. Also, GCSC is added with TPG to damp the signal oscillation quickly and provides uninterrupted capacitive reactance without the threat of resonance. Parameters of GCSC are optimized using hybrid crow search and nelder mead algorithm. Dynamic simulation based on time domain is carried out on nonlinear model to find dynamic stability under different system disturbances whereas eigenvalue analysis based on frequency domain is performed to define steady-state steadiness under different tidal speeds. The proposed investigation is confirmed on the multi-machine system. © 2023 IEEE.

关键词： Crow search algorithm gate controlled series capacitor nelder mead algorithm tidal power generation

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Design and shape optimization of MR brakes using nelder-mead optimization algorithm

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MECHANICS & INDUSTRY 2019年第6期20卷

作者： Bazargan-Lari, Yousef Islamic Azad Univ Shiraz Branch Dept Mech Engn Shiraz Iran

Magnetorheological (MR) brakes have attracted many attentions for controlling mechanical systems such as robots, e-bicycles, and haptic devices. A large number of researchers have delved into enhancing MR brake effectiveness. Herein, a new MR brake is proposed in which the braking torque is improved and the configuration is simplified. Numerical simulations were based on finite element method (FEM) was employed to achieve the brake model. In order to verify the obtained results, they were compared with the available ones in the literature and they have a good agreement with each other. Then, the proper brake model was optimized using nelder mead optimization algorithm. Results demonstrated 215.75 N m braking torque in the present prototype which is almost 73% higher than the previous model in the literature. In addition, the brake could induce about 125.06 N m torque on the brake disk with nearly half of the coil current used in the previous work. Besides, increase in the number of the disks was not necessarily improved braking efficiency and the size of the MR fluid gaps also influenced the brake operation. In addition, the proposed model in this paper has ease manufacturing procedure which would reduce the fabrication costs.

关键词： Brake system MR brake MR fluid optimization nelder mead algorithm FEM

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A Direct Search nelder mead MPPT based Induction Motor Drive for Solar PV Water Pumping Systems 22

A Direct Search Nelder Mead MPPT based Induction Motor Drive...

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22nd National Power Systems Conference (NPSC)

作者： Swetha, K. T. Reddy, Barry Venugopal Jain, Rohit Kumar Natl Inst Technol Dept Elect & Elect Engn Veling Goa India

ISBN: (纸本)9781665462020

This paper presents a nelder mead (NM) approach for solar photovoltaic (SPV) array-based water pumping systems (WPS) to achieve maximum power point tracking (MPPT). The conventional MPPT algorithms fail to track global MPPT under partial shading conditions. The NM algorithm mainly consists of four operations (reflection, expansion, contraction, and shrinkage) which aid in the rapid convergence of all the particles to a global optimum. This results in a negligible steadystate error. The two-stage PV system is modeled and simulated in MATLAB/Simulink. To verify the effectiveness of the proposed system, it is compared with the perturb and observe and particle swarm optimization method. The NM algorithm converges in an average time duration of 0.25 s with an efficiency of 99.85%. The proposed two-stage system performance has been improved with the reduction in steady-state oscillation when compared with the conventional method.

关键词： Maximum power point tracking (MPPT) nelder mead algorithm Partial shading condition (PSC) Photovoltaic (PV) Sine pulse width modulation (PWM) V/f control

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Thermal Analysis of Conductive-Convective-Radiative Heat Exchangers With Temperature Dependent Thermal Conductivity

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IEEE ACCESS 2021年 9卷 138876-138902页

作者： Khan, Naveed Ahmad Sulaiman, Muhammad Kumam, Poom Abu Bakar, Maharani Abdul Wali Khan Univ Mardan Dept Math Mardan 23200 Khyber Pakhtunk Pakistan King Mongkuts Univ Technol Thonburi KMUTT Fac Sci Dept Math KMUTT Fixed Point Res LabKMUTT Fixed Point Theor Bangkok 10140 Thailand King Mongkuts Univ Technol Thonburi KMUTT Ctr Excellence Theoret & Computat Sci TaCS CoE Bangkok 10140 Thailand China Med Univ China Med Univ Hosp Dept Med Res Taichung 40402 Taiwan Univ Malaysia Terengganu Fac Ocean Engn Technol & Informat Special Interest Grp Modelling & Data Analyt Terengganu 21300 Malaysia

In this paper, one dimensional mathematical model of convective-conductive-radiative fins is presented with thermal conductivity depending on temperature. The temperature field with insulated tip is determined for a fin in convective, conductive and radiative environments. Moreover, an intelligent soft computing paradigm named as the LeNN-WOA-NM algorithm is designed to analyze the mathematical model for the temperature field of convective-conductive-radiative fins. The proposed algorithm uses function approximating ability of Legendre polynomials based on artificial neural networks (ANN's), global search optimization ability of Whale optimization algorithm (WOA), and local search convergence of nelder-mead algorithm. The proposed algorithm is applied to illustrate the effect of variations in coefficients of convection, radiation heat losses, and dimensionless parameter of thermal conductivity on temperature distribution of conductive-convective and radiative fins in convective and radiative environments. The experimental data establishes the effectiveness of the design scheme when compared with techniques in the latest literature. It can be observed that accuracy of approximate temperature increases with lower values of N-c and N-r while decreases with increase in lambda. The quality of solutions obtained by LeNN-WOA-NM algorithm are validated through performance indicators including absolute errors, MAD, TIC, and ENSE.

关键词： Conductive-convective-radiative fin temperature-dependent thermal conductivity temperature distribution weighted Legendre neural networks hybrid soft computing whale optimization algorithm nelder mead algorithm

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Nonlinear model predictive control based on nelder mead optimization method

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NONLINEAR DYNAMICS 2018年第2期92卷 127-138页

作者： Chagra, Wassila Degachi, Hajer Ksouri, Moufida Tunis El Manar Univ El Manar Preparatory Inst Engn Studies LR11ES20 Anal Concept & Control Syst Lab BP 37 Belvedere Tunis 1002 Tunisia Tunis El Manar Univ Natl Engn Sch Tunis LR11ES20 Anal Concept & Control Syst Lab Tunis Tunisia

In this paper, a model predictive control (MPC) scheme based on Hammerstein model is carried on. The use of such nonlinear models complicates the implementation of the MPC in terms of computational time and burden since a nonlinear and so a nonconvex optimization problem will result. The nelder mead (NM) algorithm, as a free derivative method, is used to solve the resulting optimization problem. NM algorithm proves its efficiency in terms of computation time and global optimum seeking that can be successfully exploited especially with fast dynamic systems. A comparative study between the NM algorithm and the gradient-based method (GBM) based on computation time is established. The efficiency of the NM algorithm is illustrated with SISO and MIMO examples compared to GBM algorithm.

关键词： Model predictive control Hammerstein model Optimization nelder mead algorithm Gradient method Computation time

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A novel vibration based breathing crack localization technique using a single sensor measurement

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2019年 122卷 117-138页

作者： Prawin, J. Lakshmi, K. Rao, A. Rama Mohan CSIR Struct Engn Res Ctr CSIR Campus Chennai TN India

Structural damages such as a fatigue-breathing crack can result in nonlinear dynamical signatures that can significantly enhance their detection. Majority of the existing vibration based breathing crack diagnosis techniques demands rather a dense sensor network in order to detect, precisely locate the spatial location and characterize the breathing crack as the change in the dynamic characteristics of a structure with breathing crack is much smaller when compared to open cracks of the same magnitude. Further, the quality of identification improves with the increase in the number of sensors. In this paper, a novel vibration-based damage detection technique based on the zero strain energy nodes concept is proposed for the first time to identify the exact spatial location of the breathing crack using a single sensor measurement. Two different procedures based on sweep sine and harmonic excitation are outlined for breathing crack localization. Multi-level Singular Spectrum Analysis (M-SSA) is used in the present work to conclude about the presence of nonlinear behaviour of the structure and also for the identification of frequencies at which the cracked structure behaves linearly. Numerical and experimental investigations presented in this paper clearly establish that the proposed approach has the ability to identify single and as well as multiple breathing cracks present anywhere in the structure even with noise contaminated measurements. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Breathing crack Superharmonics Spectral density function Nonlinearity Curvature Singular spectrum analysis Pairwise eigenvalues Zero strain energy nodes Particle swarm optimisation nelder mead algorithm

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Optimal Design of an Intelligent Mobile Microcontroller: Assembling and Maintaining Objects in 3D

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AIN SHAMS ENGINEERING JOURNAL 2019年第2期10卷 403-410页

作者： Abbas, Mohamed AbdElhamid King Khalid Univ Coll Engn Elect Engn Dept POB 960 Asir Abha 61421 Saudi Arabia Delta Univ Sci & Technol Dept Comp & Commun Coll Eng Belkas Dakahlia Govern Egypt

Mobile microcontrollers are one of the areas of application artificial intelligent. The aim of this research is to develop an ideal design for mobile microcontrollers can move in a vacuum in order to conduct the installation with little cost. This design of mobile microcontrollers gives them the ability to move an arm with high starting torque enable it to perform their tasks efficiently. The main objective of this paper is to present an optimal design of mobile microcontrollers have an arm with high starting torque and with low cost. To verify this objective, nelder mead simplex search algorithm is used to obtain the optimal values of manufacturing parameters. The results depict a reduction of the total cost that represents cost of unit weight of copper, cost of unit weight of iron, the laminations cost, the copper cost and the rotor-end-ring cost by 4.64% and a reduction in the angular velocity by 25%. (C) 2019 The Author. Published by Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University.

关键词： Mobile microcontrollers Robotic arm Induction motor nelder mead algorithm Starting torque Motor cost

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Off-Grid Sparse Estimator for Air Velocity in Missing-Data Case

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JOURNAL OF AIRCRAFT 2016年第3期53卷 768-777页

作者： Yu Fei Tao Jian-wu Zhang Qing-jie Naval Aeronaut & Astronaut Univ Dept Control Engn Yantai 264001 Peoples R China Aviat Univ Air Force Dept Aircraft Control Engn Changchun 130022 Peoples R China Acad Armament Beijing 100161 Peoples R China

This paper addresses the problem of estimating the supersonic air velocity from an incomplete measurement of an acoustic sensor array, that is, when some of the data are missing. Most sparsity-inducing estimators for air velocity require the discretization of the estimation grid. When the true air velocity is not on the discretized grid, this leads to grid mismatch, which results in a degradation of the performance. To deal with such an off-grid air velocity estimation problem, an off-grid, iteratively stochastic maximum-likelihood algorithm of estimating air velocity (abbreviated as Sparse Asymptotic Minimum Variance-Stochastic Maximum Likelihood-Air Velocity Estimation) is proposed, based on sparse asymptotic minimum-variance criterion. The proposed algorithm can achieve the off-grid air velocity estimation with high accuracy, eliminating the need of additional grid-refinement techniques. Compared with other off-the-shelf sparse estimation methods, the proposed algorithm is computationally more efficient. Moreover, the proposed algorithm is suitable for estimating the air velocity in case of missing data. Simulations are implemented to illustrate the effectiveness of the proposed algorithm.

关键词： Acoustic Vector Sensor Supersonic Flow Singular Value Decomposition Mach Angle Supersonic Flight Computing MATLAB Line of Sight Propagation Rayleigh Distribution nelder mead algorithm

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Modeling of Dispersive Materials Using Dispersion Models for FDTD Application

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SILICON 2016年第2期8卷 251-275页

作者： Sagor, Rakibul Hasan Shahriar, Kh. Arif Saber, Md. Ghulam Joy, Md. Mahamudun Arif Sohel, Ikramul Hasan Islamic Univ Technol Dept Elect & Elect Engn Gazipur 1704 Bangladesh Northern Univ Bangladesh Dept Elect & Elect Engn Sher TowerHolding 13Rd 17 Dhaka 1213 Bangladesh Bangladesh Univ Business & Technol Dept Elect & Elect Engn Plot 77-78Rd 9Mirpur 2 Dhaka 1216 Bangladesh

A nonlinear optimization algorithm based on the nelder mead method is used to characterize the frequency dependent permittivity of 15 materials based on Lorentz, modified Lorentz, Drude and Lorentz-Drude models. The optimized model parameters are used to calculate the complex relative permittivity of each material and compare it with experimental data. In each case, a very good match is found between the optimized and experimental data over a long wavelength range. Comparative study of the models used for each material is performed based on accuracy, wavelength range of applicability and computational efficiency. The parameters presented can be used for computer simulation of electromagnetic wave phenomena involving these materials.

关键词： Material dispersion Lorentz model Modified Lorentz model Lorentz-Drude model Drude model Optical properties Material modeling nelder mead algorithm Finite-Difference time-domain

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Nonlinear parametric identification strategy combining reverse path and hybrid dynamic quantum particle swarm optimization

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NONLINEAR DYNAMICS 2016年第2期84卷 797-815页

作者： Prawin, J. Rao, A. Rama Mohan Lakshmi, K. Acad Sci & Innovat Res CSIR Campus Madras Tamil Nadu India CSIR Struct Engn Res Ctr CSIR Campus Madras Tamil Nadu India

Parametric identification procedures for linear systems are fairly well established. However, there are only a few methods capable of identifying parametric models for multiple degree of freedom nonlinear systems. In this paper, we propose a three-stage parametric identification algorithm for nonlinear systems. Using the proposed algorithm, it is possible to detect the presence and the location of nonlinear attachment as well as the system parameters, to a very good level of accuracy. Numerical simulation studies have been carried out to test and verify the effectiveness of the proposed algorithm.

关键词： Nonlinearity System identification Null subspace Reverse path method Meta-heuristic algorithm Quantum PSO nelder mead algorithm

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