Segmental transmission line: Its practical application the optimized PCB trace design using a genetic algorithm

2014 ◽  
Author(s):  
Moritoshi Yasunaga ◽  
Hiroki Shimada ◽  
Katsuyuki Seki ◽  
Ikuo Yoshihara
Keyword(s):  
Genetic Algorithm ◽  
Transmission Line ◽  
Practical Application

scholarly journals Developing Induction Motor State Observers with Increased Robustness

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5487
Author(s):  
Tadeusz Białoń ◽  
Marian Pasko ◽  
Roman Niestrój
Keyword(s):  
Genetic Algorithm ◽  
Control Theory ◽  
Induction Motor ◽  
Optimization Method ◽  
Practical Application ◽  
Proportional Integral ◽  
State Observers ◽  
Simulation Results ◽  
Selection Of

This paper presents the results of recently conducted research on Luenberger observers with non-proportional feedbacks. The observers are applied for the reconstruction of magnetic fluxes of an induction motor. Structures of the observers known from the control theory are presented. These are a proportional observer, a proportional-integral observer, a modified integral observer, and an observer with additional integrators. The practical application of some of these observers requires modifications to their structures. In the paper, the simulation results for all mentioned types of observers are presented. The simulations are performed with a Scilab-Xcos model which is attached to this paper. The problem of gains selection of the observers is discussed. Gains are selected with the described optimization method based on a genetic algorithm. A Scilab file launching the genetic algorithm also is attached to this paper.

OPTIMIZATION OF MODIFIED WATT’S LINKAGE FOR AN APPROXIMATELY LONG STRAIGHT PATH WITHIN LIMITED DIMENSION

2016 ◽  
Vol 40 (3) ◽  
pp. 399-417
Author(s):  
Jun Wu ◽  
Shaowei Fan ◽  
Minghe Jin ◽  
Hong Liu
Keyword(s):  
Genetic Algorithm ◽  
Constrained Optimization ◽  
Synthesis Process ◽  
Path Generation ◽  
Practical Application ◽  
Optimal Method ◽  
Kinematic Synthesis ◽  
Straight Path ◽  
Limited Dimension

This paper presents an optimal method of aiming for an approximately straight path of the Modified Watt’s Linkage (MWL) within limited dimension. A modification to the Watt’s linkage and the corresponding condition are introduced, followed by the kinematic synthesis. The path generation based on the modification considering constraints from practical application is provided. Genetic algorithm is utilized to perform the constrained optimization. The centrosymmetric property of the MWL is considered in the synthesis process. Ideal parameters of the mechanism are achieved to demonstrate the effectiveness of the proposed method.

Predicting Credit Ratings with a GA-MLP Hybrid

2006 ◽  
pp. 220-238 ◽  
Author(s):  
Robert Perkins ◽  
Anthony Brabazon
Keyword(s):  
Genetic Algorithm ◽  
Evolutionary Algorithm ◽  
Credit Ratings ◽  
Corporate Bond ◽  
Practical Application ◽  
Bond Issuers

The practical application of MLPs can be time-consuming due to the requirement for substantial modeler intervention in order to select appropriate inputs and parameters for the MLP. This chapter provides an example of how elements of the task of constructing a MLP can be automated by means of an evolutionary algorithm. A MLP whose inputs and structure are automatically selected using a genetic algorithm (GA) is developed for the purpose of predicting corporate bond-issuer ratings. The results suggest that the developed model can accurately predict the credit ratings assigned to bond issuers.

scholarly journals Optimal location of unified power flow controller genetic algorithm based

2020 ◽  
Vol 11 (2) ◽  
pp. 886
Author(s):  
Sana Khalid Abdul Hassan ◽  
Firas Mohammed Tuaimah
Keyword(s):  
Genetic Algorithm ◽  
Power Generation ◽  
Power System ◽  
Transmission Line ◽  
Transmission Lines ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Optimal Location ◽  
Power Losses

<p>Now-a-days the Flexible AC Transmission Systems (FACTS) technology is very effective in improving the power flow along the transmission lines and makes the power system more flexible and controllable. This paper deals with overload transmission system problems such as (increase the total losses, raise the rate of power generation, and the transmission line may be exposed to shut down when the load demand increase from the thermal limit of transmission line) and how can solve this problem by choosing the optimal location and parameters of Unified Power Flow Controllers (UPFCs). which was specified based on Genetic Algorithm (GA) optimization method, it was utilized to search for optimum FACT parameters setting and location based to achieve the following objectives: improve voltages profile, reduce power losses, treatment of power flow in overloaded transmission lines and reduce power generation. MATLAB was used for running both the GA program and Newton Raphson method for solving the load flow of the system The proposed approach is examined and tested on IEEE 30-bus system. The practical part has been solved through Power System Simulation for Engineers (PSS\E) software Version 32.0 (The Power System Simulator for Engineering (PSS/E) software created from Siemens PTI to provide a system of computer programs and structured data files designed to handle the basic functions of power system performance simulation work, such as power flow, optimal power flow, fault analysis, dynamic simulations...etc.). The Comparative results between the experimental and practical parts obtained from adopting the UPFC where too close and almost the same under different loading conditions, which are (5%, 10%, 15% and 20%) of the total load. can show that the total active power losses for the system reduce at 69.594% at normal case after add the UPFC device to the system. also the reactive power losses reduce by 75.483% at the same case as well as for the rest of the cases. in the other hand can noted the system will not have any overload lines after add UPFC to the system with suitable parameters.</p>

scholarly journals Practical Application of Long-term Bridge Management System Using Genetic Algorithm

2011 ◽  
Vol 23 (4) ◽  
pp. 469-479 ◽  
Author(s):  
Koichiro NAKATSU ◽  
Hitoshi FURUTA ◽  
Yasutoshi NOMURA ◽  
Kyosuke TAKAHASHI ◽  
Ken ISHIBASHI ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Management System ◽  
Bridge Management ◽  
Practical Application ◽  
Bridge Management System
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