scholarly journals Nonlinear Optimization Methods for Large-Scale Learning

2019 ◽  
Author(s):  
Jorge Nocedal
Keyword(s):  
Nonlinear Optimization ◽  
Large Scale ◽  
Optimization Methods ◽  
Large Scale Learning ◽  
Nonlinear Optimization Methods

scholarly journals Optimization of the cross-sectional shape of the belts of trihedral lattice supports

2019 ◽  
Vol 7 (4) ◽  
pp. 5-8
Author(s):  
Linar Sabitov ◽  
Ilnar Baderddinov ◽  
Anton Chepurnenko
Keyword(s):  
Objective Function ◽  
Nonlinear Optimization ◽  
Cross Section ◽  
Optimization Methods ◽  
Cross Sectional ◽  
Maximum Value ◽  
Axial Moment ◽  
The Cross ◽  
Nonlinear Optimization Methods ◽  
Sectional Shape

The article considers the problem of optimizing the geometric parameters of the cross section of the belts of a trihedral lattice support in the shape of a pentagon. The axial moment of inertia is taken as the objective function. Relations are found between the dimensions of the pentagonal cross section at which the objective function takes the maximum value. We introduce restrictions on the constancy of the consumption of material, as well as the condition of equal stability. The solution is performed using nonlinear optimization methods in the Matlab environment.

scholarly journals Calibration of a Nonlinear DC Motor under Uncertainty Using Nonlinear Optimization Techniques

2021 ◽  
Vol 65 (1) ◽  
pp. 42-52
Author(s):  
Hamed Keshmiri Neghab ◽  
Hamid Keshmiri Neghab
Keyword(s):  
Nonlinear Optimization ◽  
Model Calibration ◽  
Optimization Methods ◽  
Dc Motor ◽  
Optimization Techniques ◽  
Unknown Parameters ◽  
Labview Software ◽  
Dc Motors ◽  
Industrial Software ◽  
Nonlinear Optimization Methods

The use of DC motors is increasingly high and it has more parameters which should be normalized. Now the calibration of each parameters is important for each motor, because it affects in its performance and accuracy. A lot of researches are investigated in this area. In this paper demonstrated how to estimate the parameters of a Nonlinear DC Motor using different Nonlinear Optimization techniques of fitting parameters to model, that called model calibration. First, three methods for calibration of a DC motor are defined, then unknown parameters of the mathematical model with the nonlinear optimization techniques for the fitting routines and model calibration process, are identified. In addition, three optimization techniques such as Levenberg-Marquardt, Constrained Nonlinear Optimization and Gauss-Newton, are compared. The goal of this paper is to estimate nonlinear parameters of a DC motor under uncertainty with nonlinear optimization methods by using LabVIEW software as an industrial software and compare the nonlinear optimization methods based on position, velocity and current. Finally, results are illustrated and comparison between these methods based on the results are made.

Crashworthy structures for future vehicle architecture of autonomous pods and heavy quadricycles on public roads: A review

2019 ◽  
Vol 234 (1) ◽  
pp. 3-16
Author(s):  
Andrew Harrison ◽  
Jesper Christensen ◽  
Christophe Bastien ◽  
Stratis Kanarachos
Keyword(s):  
Nonlinear Optimization ◽  
Design Methodology ◽  
Significant Risk ◽  
Optimization Methods ◽  
Functionally Graded ◽  
Vehicle Architecture ◽  
Design Methodologies ◽  
Expensive Problems ◽  
Computationally Expensive ◽  
Nonlinear Optimization Methods

With the development and deployment of lightweight vehicles to the market, inclusive of autonomous pods, a review of advanced crashworthy structures and the design methodology has been conducted as it is thought that super-lightweight vehicles may pose significant risk to the occupants if they are involved in a crash. It is suggested that tests should include oblique and multiple velocity impacts to cater for the effects of assisted driving systems of future vehicles. A review of current crash structures and design methodologies revealed that the most recent research do not cater to multiple crash scenarios, nor a shorter crush allowance, therefore resulting in poor crashworthiness performance. In addition, the arbitrary seat positioning shown in autonomous pods’ concepts vastly increases the risk to occupants. Greater enhancements to passive crashworthiness are imperative. To this end, functionally graded vehicle structures should be designed as it has been found that these can provide optimized solutions. Research into nonlinear optimization methods for computationally expensive problems will become central to this.

Nonlinear optimization methods applied to magnetic actuators design

1992 ◽  
Vol 28 (2) ◽  
pp. 1581-1584 ◽  
Author(s):  
R.R. Saldanha ◽  
S. Pelissier ◽  
K. Kadded ◽  
Y.P. Yonnet ◽  
J.-L. Coulomb
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Methods ◽  
Magnetic Actuators ◽  
Nonlinear Optimization Methods

Numerical Optimization of a Gas Turbine Cogeneration Plant

2003 ◽  
Author(s):  
Jose´ C. F. Teixeira ◽  
Senhorinha F. C. F. Teixeira ◽  
Aˆngela M. E. Silva
Keyword(s):  
Nonlinear Optimization ◽  
Gas Turbine ◽  
Heat Recovery ◽  
Optimization Methods ◽  
Thermodynamic Quantities ◽  
Cogeneration Plant ◽  
Fortran Code ◽  
Cogeneration System ◽  
Nonlinear Optimization Methods ◽  
Textile Factory

Amongst the various alternatives for the combined production of heat and power, the systems based on a gas turbine are becoming increasingly attractive. In addition to the high thermal efficiency, they can also operate on a wide variety of fuels. The basic configuration of a simple cogeneration system consisting of a gas turbine and a heat recovery steam generator has been used to illustrate the application of nonlinear optimization numerical methods as a tool to evaluate and optimize complex energy systems. The problem was formulated as the minimization of costs as the objective function, subject to the constraints imposed by the physical and thermodynamic quantities. Two numerical nonlinear optimization methods with constraints have been tested using a Fortran code and the MATLAB® environment. The model has been evaluated on a real cogeneration plant consisting of a gas turbine heat recovery system of a local textile factory.

scholarly journals Genetic Algorithm Application in Optimization of Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Ali Norouzi ◽  
A. Halim Zaim
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Fitness Function ◽  
Optimization Methods ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Final Formula ◽  
Nonlinear Optimization Methods

There are several applications known for wireless sensor networks (WSN), and such variety demands improvement of the currently available protocols and the specific parameters. Some notable parameters are lifetime of network and energy consumption for routing which play key role in every application. Genetic algorithm is one of the nonlinear optimization methods and relatively better option thanks to its efficiency for large scale applications and that the final formula can be modified by operators. The present survey tries to exert a comprehensive improvement in all operational stages of a WSN including node placement, network coverage, clustering, and data aggregation and achieve an ideal set of parameters of routing and application based WSN. Using genetic algorithm and based on the results of simulations in NS, a specific fitness function was achieved, optimized, and customized for all the operational stages of WSNs.

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