• Title/Summary/Keyword: Fitness Function Modeling

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Sliding Mode Controller with Sliding Perturbation Observer Based on Gain Optimization using Genetic Algorithm

  • You, Ki-Sung;Lee, Min-Cheol;Yoo, Wan-Suk
    • Journal of Mechanical Science and Technology
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    • v.18 no.4
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    • pp.630-639
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    • 2004
  • The Stewart platform manipulator is a closed-kinematics chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. However, this is a complex and nonlinear system, so the control performance of the system is not so good. In this paper, a new robust motion control algorithm is proposed. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is the design of a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observe. (SMCSPO). The optimal gains of SMCSPO, which is determined by nominal eigenvalues, are easily obtained by genetic algorithm. The proposed fitness function that evaluates the gain optimization is to put sliding function. The control performance of the proposed algorithm is evaluated by the simulation and experiment to apply to the Stewart platform. The results showed high accuracy and good performance.

An Arrangement Technique for Fine Regular Triangle Grid of Network Dome by Using Harmony Search Algorithm (화음탐색 알고리즘을 이용한 네트워크 돔의 정삼각형 격자 조절기법)

  • Shon, Su-Deok;Jo, Hye-Won;Lee, Seung-Jae
    • Journal of Korean Association for Spatial Structures
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    • v.15 no.2
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    • pp.87-94
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    • 2015
  • This paper aimed at modeling a fine triangular grid for network dome by using Harmony Search (HS) algorithm. For this purpose, an optimization process to find a fine regular triangular mesh on the curved surface was proposed and the analysis program was developed. An objective function was consist of areas and edge's length of each triangular and its standard deviations, and design variables were subject to the upper and lower boundary which was calculated on the nodal connectivity. Triangular network dome model, which was initially consist of randomly irregular triangular mesh, was selected for the target example and the numerical result was analyzed in accordance with the HS parameters. From the analysis results of adopted model, the fitness function has been converged and the optimized triangular grid could be obtained from the initially distorted network dome example.

The Application of Genetic Algorithm for the Identification of Discontinuity Sets (불연속면 군 분류를 위한 유전자알고리즘의 응용)

  • Sunwoo Choon;Jung Yong-Bok
    • Tunnel and Underground Space
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    • v.15 no.1 s.54
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    • pp.47-54
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    • 2005
  • One of the standard procedures of discontinuity survey is the joint set identification from the population of field orientation data. Discontinuity set identification is fundamental to rock engineering tasks such as rock mass classification, discrete element analysis, key block analysis. and discrete fracture network modeling. Conventionally, manual method using contour plot had been widely used for this task, but this method has some short-comings such as yielding subjective identification results, manual operations, and so on. In this study, the method of discontinuity set identification using genetic algorithm was introduced, but slightly modified to handle the orientation data. Finally, based on the genetic algorithm, we developed a FORTRAN program, Genetic Algorithm based Clustering(GAC) and applied it to two different discontinuity data sets. Genetic Algorithm based Clustering(GAC) was proved to be a fast and efficient method for the discontinuity set identification task. In addition, fitness function based on variance showed more efficient performance in finding the optimal number of clusters when compared with Davis - Bouldin index.

Genetic Algorithm-based Generative Design for Creative Ring Design (독창적 반지 설계를 위한 유전자 알고리즘 기반의 변환생성 디자인)

  • Kim, Ko Uh;Kang, Sol Ji;Jee, Sang Hyeon;Lee, Seung Bok;Lee, Keon Myung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.3
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    • pp.233-238
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    • 2014
  • Creativity is crucial in designing and producing attractive accessaries and daily supplies as well as art works. Generative design can be a paradigm to be used to obtain novel ideas or motifs for creative design works. This paper introduces a generative design method which comes up with unique ring models using genetic algorithm. It presents how the genetic algorithm works in terms of candidate solution coding, operators, and fitness evaluation function. The proposed method allows the customers to express their personal preference and later the preference to be reflected in fitness evaluation. In the final stage of the proposed method, several ring models are suggested for customers to choose on their own. The chosen ring models can be put into physical rings with the help of a 3D printer because the models are expressed in 3D geometric structures.

A Comparative Study on the Genetic Algorithm and Regression Analysis in Urban Population Surface Modeling (도시인구분포모형 개발을 위한 GA모형과 회귀모형의 적합성 비교연구)

  • Choei, Nae-Young
    • Spatial Information Research
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    • v.18 no.5
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    • pp.107-117
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    • 2010
  • Taking the East-Hwasung area as the case, this study first builds gridded population data based on the municipal population survey raw data, and then measures, by way of GIS tools, the major urban spatial variables that are thought to influence the composition of the regional population. For the purpose of comparison, the urban models based on the Genetic Algorithm technique and the regression technique are constructed using the same input variables. The findings indicate that the GA output performed better in differentiating the effective variables among the pilot model variables, and predicted as much consistent and meaningful coefficient estimates for the explanatory variables as the regression models. The study results indicate that GA technique could be a very useful and supplementary research tool in understanding the urban phenomena.

Fuzzy Model Identification using a mGA Hybrid Schemes (mGA의 혼합된 구조를 사용한 퍼지 모델 동정)

  • Ju, Yeong-Hun;Lee, Yeon-U;Park, Jin-Bae
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.8
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    • pp.423-431
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    • 2000
  • This paper presents a systematic approach to the input-output data-based fuzzy modeling for the complex and uncertain nonlinear systems, in which the conventional mathematical models may fail to give the satisfying results. To do this, we propose a new method that can yield a successful fuzzy model using a mGA hybrid schemes with a fine-tuning method. We also propose a new coding method fo chromosome for applying the mGA to the structure and parameter identifications of fuzzy model simultaneously. During mGA search, multi-purpose fitness function with a penalty process is proposed and adapted to guarantee the accurate and valid fuzzy modes. This coding scheme can effectively represent the zero-order Takagi-Sugeno fuzzy model. The proposed mGA hybrid schemes can coarsely optimize the structure and the parameters of the fuzzy inference system, and then fine tune the identified fuzzy model by using the gradient descent method. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its applications to two nonlinear systems.

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Kinetic Modeling for Quality Prediction During Kimchi Fermentation

  • Chung, Hae-Kyung;Yeo, Kyung-Mok;Kim, Nyung-Hwan
    • Preventive Nutrition and Food Science
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    • v.1 no.1
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    • pp.41-45
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    • 1996
  • This study was conducted to develop the fermentation kinetic model for the prediction of acidity and pH changes in Kimchi as a function of fermentation temperatures. The fitness of the model was evaluated using traditional two-step method and an alternative non-linear regression method. The changes in acidity and pH during fermentation followed the pattern of the first order reaction of a two-step method. As the fermentation temperature increased from 4$^{\circ}C$ to 28, the reaction rates of acidity and pH were increased 8.4 and 7.6 times, respectively. The activation energies of acidity and pH were 16.125 and 16.003kcal/mole. The average activation energies of acidity and pH using a non-linear method were 16.006 by the first order and 15.813 kcal/mole by the zero order, respectively. The non-linear procedure had better fitting 개 experimental data of the acidity and pH than two-step method. The shelf-lives based on the time to reach the 1.0% of acidity were 33.1day at 4$^{\circ}C$ and 2.8 day 28$^{\circ}C$.

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Genetic Algorithm based Pathfinding System for Analyzing Networks (네트워크 분석을 위한 유전 알고리즘 기반 경로탐색 시스템)

  • Kim, Jun-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.1
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    • pp.119-130
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    • 2014
  • This paper proposes GAPS, a practical genetic algorithm based pathfinding system for conveniently analyzing various networks. To this end, the GAPS is developed through integration of the intuitive graphic user interface for network modeling, the database management system for managing the data generated in modeling and exploring procedures, and a simple genetic algorithm for analyzing a wide range of networks. Especially, previous genetic algorithms are not appropriate for analyzing the networks with many dead-ends where there are few feasible paths between the given two nodes, however, GAPS is based on the genetic algorithm with the fitness function appropriate for evaluating both feasible and infeasible paths, which enables GAPS to analyze a wide range of networks while maintaining the diversity of the population. The experiment results reveal that GAPS can be used to analyze both networks with many dead-ends and networks with few dead-ends conveniently, and GAPS has several advantages over the previous genetic algorithms for pathfinding problems.

Design of RBFNN-based Emotional Lighting System Using RGBW LED (RGBW LED 이용한 RBFNN 기반 감성조명 시스템 설계)

  • Lim, Sung-Joon;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.5
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    • pp.696-704
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    • 2013
  • In this paper, we introduce the LED emotional lighting system realized with the aid of both intelligent algorithm and RGB LED combined with White LED. Generally, the illumination is known as a design factor to form the living place that affects human's emotion and action in the light- space as well as the purpose to light up the specific space. The LED emotional lighting system that can express emotional atmosphere as well as control the quantity of light is designed by using both RGB LED to form the emotional mood and W LED to get sufficient amount of light. RBFNNs is used as the intelligent algorithm and the network model designed with the aid of LED control parameters (viz. color coordinates (x and y) related to color temperature, and lux as inputs, RGBW current as output) plays an important role to build up the LED emotional lighting system for obtaining appropriate color space. Unlike conventional RBFNNs, Fuzzy C-Means(FCM) clustering method is used to obtain the fitness values of the receptive function, and the connection weights of the consequence part of networks are expressed by polynomial functions. Also, the parameters of RBFNN model are optimized by using PSO(Particle Swarm Optimization). The proposed LED emotional lighting can save the energy by using the LED light source and improve the ability to work as well as to learn by making an adequate mood under diverse surrounding conditions.