scholarly journals Threshold Tuning Method for Color Extraction Processing Used Genetic Algorithm

2007 ◽  
Vol 19 (5) ◽  
pp. 514-523
Author(s):  
Yoichiro MAEDA ◽  
Masashi ISHIKAWA
Keyword(s):  
Genetic Algorithm ◽  
Tuning Method ◽  
Threshold Tuning

scholarly journals Genetic algorithm hyper-parameter optimization using Taguchi design for groundwater pollution source identification

2018 ◽  
Vol 19 (1) ◽  
pp. 137-146 ◽  
Author(s):  
Xuemin Xia ◽  
Simin Jiang ◽  
Nianqing Zhou ◽  
Xianwen Li ◽  
Lichun Wang
Keyword(s):  
Genetic Algorithm ◽  
Groundwater Pollution ◽  
Parameter Tuning ◽  
Pollution Source ◽  
Heterogeneous Porous Media ◽  
Optimization Approach ◽  
Human Beings ◽  
Transient Transport ◽  
Tuning Method ◽  
Pollutant Source

Abstract Groundwater pollution has been a major concern for human beings, since it is inherently related to people's health and fitness and the ecological environment. To improve the identification of groundwater pollution, many optimization approaches have been developed. Among them, the genetic algorithm (GA) is widely used with its performance depending on the hyper-parameters. In this study, a simulation–optimization approach, i.e., a transport simulation model with a genetic optimization algorithm, was utilized to determine the pollutant source fluxes. We proposed a robust method for tuning the hyper-parameters based on Taguchi experimental design to optimize the performance of the GA. The effectiveness of the method was tested on an irregular geometry and heterogeneous porous media considering steady-state flow and transient transport conditions. Compared with traditional GA with default hyper-parameters, our proposed hyper-parameter tuning method is able to provide appropriate parameters for running the GA, and can more efficiently identify groundwater pollution.

An efficient Threshold tuning Method of OCM based M/M/1 queue

2013 ◽  
Author(s):  
Xiaochun Yin ◽  
◽  
Hoon Jae Lee ◽  
Keyword(s):  
Tuning Method ◽  
Threshold Tuning

Threshold tuning method for arrays of split-gate nanostructure transistors in series

2014 ◽  
Author(s):  
Haider Al-Taie ◽  
Luke W. Smith ◽  
Reuben K. Puddy ◽  
Patrick See ◽  
Jonathan P. Griffiths ◽  
...  
Keyword(s):  
Tuning Method ◽  
In Series ◽  
Threshold Tuning

Optimal PI Controller Tuning Based on ITAE Criterion for Low-Order Systems with Large Time Delay

2013 ◽  
Vol 411-414 ◽  
pp. 1716-1719
Author(s):  
Feng Ping Pan ◽  
Hong Kai Liao ◽  
Jia Luo ◽  
Xi Zhang
Keyword(s):  
Genetic Algorithm ◽  
Time Delay ◽  
Large Time ◽  
Pi Controller ◽  
Stable Region ◽  
Controller Tuning ◽  
Nonlinear Fitting ◽  
Tuning Method ◽  
Tuning Methods ◽  
Low Order

For low order process with large time delay, a kind of optimal PI controller tuning method is proposed based on generalized Hermite-Biehler theorem and Genetic Algorithm. Firstly, the stable region of PI controller is obtained by using the generalized Hermite-Biehler theorem. Then the optimum parameters are selected from this region based on ITAE criterion and genetic algorithm. A tuning formula is obtained by nonlinear fitting of optimization result, which has the capability to cover the variety of normalized time delays up to 100. Simulation of Monte-Carlo stochastic experiment indicates that the proposed method has good performance robustness when parameter uncertainty occurs, compared with other four PI tuning methods.

scholarly journals Implementing optimization of PID controller for DC motor speed control

2021 ◽  
Vol 23 (2) ◽  
pp. 657
Author(s):  
Yasir G. Rashid ◽  
Ahmed Mohammed Abdul Hussain
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Optimization Technique ◽  
Speed Control ◽  
Optimization Method ◽  
Dc Motor ◽  
Motor Speed ◽  
Tuning Method ◽  
Pid Tuning ◽  
Dc Motor Control

The point of this paper presents an optimization technique which is flexible and quick tuning by using a genetic algorithm (GA) to obtain the optimum proportional-integral-derivative (PID) parameters for speed control of aseparately excited DC motor as a benchmark for performance analysis. The optimization method is used for searching for the proper value of PID parameters. The speed controller of DC motor using PID tuning method sincludes three types: MATALB PID tunner app., modified Ziegler-Nicholsmethod and genetic algorithm (GA). PID controller parameters (Kp, Ki and Kd) will be obtained by GA to produce optimal performance for the DC motor control system. Simulation results indicate that the tuning method of PID by using a genetic algorithm is shown to create the finest result in system performance such as settling time, rise time, percentage of overshoot and steady state error. The MATLAB/Simulink software is used to model and simulate the proposed DC motor controller system.

scholarly journals Optimization of PID Tuning Using Genetic Algorithm

1970 ◽  
Vol 2 (2) ◽  
Author(s):  
Tengku Ahmad Faris Ku Yusoff ◽  
Mohd Farid Atan ◽  
Nazeri Abdul Rahman ◽  
Shanti Faridah Salleh ◽  
Noraziah Abdul Wahab
Keyword(s):  
Genetic Algorithm ◽  
Population Size ◽  
Rise Time ◽  
Distillation Column ◽  
Settling Time ◽  
Tuning Method ◽  
Pid Tuning ◽  
The Cost ◽  
Large Improvement

Controller tuning is one of the important aspect in industry. With a good tuning method, it can ensure the quality of the process and product produce. Apart from that, it can protect the environment and help the company to reduce the cost. Genetic algorithm is one of the tuning method that increase usage and awareness in industry. Thus, the objective of this research is to compare the performance of the conventional tuning method with the performance of tuning method by using genetic algorithm can be seen. Optimization was done on stripping section of distillation column by using genetic algorithm with population size of 20, 40, 60 and 80 and comparing the result with previous optimization using Ziegler-Nichols method. The result obtain showed large improvement in the process response especially on rise time from 1.33 s to 1.31s and settling time from 4.56 to 4.46. Finally, population size of 40 deliver the fastest rise time and settling time.

scholarly journals Coordinated Tuning of a Group of Static Var Compensators Using Multi-Objective Genetic Algorithm

2011 ◽  
Vol 14 (1) ◽  
Author(s):  
Enrique Ramón Chaparro Viveros ◽  
Manuel Leonardo Sosa Ríos
Keyword(s):  
Genetic Algorithm ◽  
Steady State ◽  
Reactive Power ◽  
Load Flow ◽  
Operating Conditions ◽  
Financial Investment ◽  
Multi Objective ◽  
Tuning Method ◽  
Static Var Compensators ◽  
Voltage Deviation

The optimal coordinated tuning of a group of Static Var Compensators (SVC), in steady state, allows the Power Electric Systems (PES) to operate close to their overload limits, maintaining the voltage stability in several operating conditions. The mentioned tuning problem was considered as a Multi- objective Optimization Problem (MOP) with three objectives to optimize: the financial investment for acquiring the set of compensators, the maximum voltage deviation and total active power loss. The Genetic Algorithm (GA), which belongs to the group of Evolutionary Algorithms, was utilized and adapted for MOP, obtaining a Multi-Objective GA (MOGA). The parameters to be adjusted in each compensator are: the reference voltage and the minimum and maximum reactive power injected to the system. In this work, the number of compensators and their locations were calculated using the Q-V sensitivity curve, from the Load Flow algorithm, based on Newton–Raphson method. The proposed coordinated tuning method will be validated considering an example of PES, where was located and tuned a specific set of compensators. Time simulations were made for dynamic performing the steady state coordinated tuning.

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