• 제목/요약/키워드: Search controller

검색결과 190건 처리시간 0.028초

퍼지로직제어에 의해 강화된 혼합유전 알고리듬 (Hybrid Genetic Algorithm Reinforced by Fuzzy Logic Controller)

  • 윤영수
    • 대한산업공학회지
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    • 제28권1호
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    • pp.76-86
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    • 2002
  • In this paper, we suggest a hybrid genetic algorithm reinforced by a fuzzy logic controller (flc-HGA) to overcome weaknesses of conventional genetic algorithms: the problem of parameter fine-tuning, the lack of local search ability, and the convergence speed in searching process. In the proposed flc-HGA, a fuzzy logic controller is used to adaptively regulate the fine-tuning structure of genetic algorithm (GA) parameters and a local search technique is applied to find a better solution in GA loop. In numerical examples, we apply the proposed algorithm to a simple test problem and two complex combinatorial optimization problems. Experiment results show that the proposed algorithm outperforms conventional GAs and heuristics.

Tabu 탐색법과 신경회로망을 이용한 SVC용 적응 퍼지제어기의 설계 (Design of Adaptive Fuzzy Logic Controller using Tabu search and Neural Network)

  • 손종훈;황기현;김형수;문경준;박준호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 A
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    • pp.34-36
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    • 2000
  • This paper proposes the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gain of input-output variables of fuzzy logic controller and weights of neural network using Tabu search. Neural network used to tune the output gain of FLC adaptively. We have weights of neural network learned using back propagation algorithm. We performed the nonlinear simulation on an single-machine infinite system to prove the efficiency of the proposed method. The proposed AFLC showed the better performance than PD controller in terms of the settling time and damping effect, for power system operation condition.

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유전 알고리즘을 이용한 전방향 신경망 제어기의 구조 최적화 (Structure Optimization of a Feedforward Neural Controller using the Genetic Algorithm)

  • 조철현;공성곤
    • 전자공학회논문지B
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    • 제33B권12호
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    • pp.95-105
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    • 1996
  • This paper presents structure optimization of a feedforward neural netowrk controller using the genetic algorithm. It is important to design the neural network with minimum structure for fast response and learning. To minimize the structure of the feedforward neural network, a genralization of multilayer neural netowrks, the genetic algorithm uses binary coding for the structure and floating-point coding for weights. Local search with an on-line learnign algorithm enhances the search performance and reduce the time for global search of the genetic algorithm. The relative fitness defined as the multiplication of the error and node functions prevents from premature convergence. The feedforward neural controller of smaller size outperformed conventional multilayer perceptron network controller.

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진화전략에 의한 PI제어기의 스폿용접기에 관한 연구 (A Study on Spot Welder of PI Controller Using Evolution Strategy)

  • 김재문;김연충;원충연;김규식
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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    • pp.531-533
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    • 1997
  • PI(proportional-integral) controller has been extensively used in the industrial field. But in practicle case, it is difficult to tune PI gains. Evolution Strategy(ES) is used as an effective search algorithm in optimization programs. In this paper we proposed a PI controller for Spot welder system using ES with varying search space. ES with varying search space which depends on fitness values at each generation is used to tune PI control parameters. Simulation results show the proposed algorithm has accurate and robust performance with effective search ability.

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Tabu Search를 이용한 TCSC의 점호각 제어용 퍼지 제어기의 설계 (Design of Fuzzy Controller for Firing Angle of TCSC Using Tabu Search)

  • 김우근;황기현;문경준;김형수;박준호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 A
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    • pp.37-39
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    • 2000
  • This paper describes the application of Fuzzy Logic Controller (FLC) to Thyristor Controlled Series Capacitor (TCSC) which can have significant impact on Power system dynamics. The function of the FLC is to control the firing angle of the TCSC. We tuned the scaling factors of the FLC using Tabu Search. The proposed FLC is used for damping the low frequency oscillations caused by disturbances such as the sudden changes of small of large loads or the outages in the generators or transmission lines. To evaluate usefulness of the proposed FLC. we performed the computer simulation for single-machine infinite system. The response of FLC is compared with that of PD controller optimized using Tabu Search. Simulation results that the FLC shows the better control performance than PD controller.

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과도 안정도 향상을 위한 TCSC의 점호각 제어용 퍼지제어기의 설계에 Tabu 탐색법의 적용 (Application of Tabu Search in Design of Fuzzy Controller for Firing Angle of TCSC Improving Transient Stability)

  • 김우근;황기현;김형수;박준호;박중근
    • 대한전기학회논문지:전력기술부문A
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    • 제50권12호
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    • pp.561-567
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    • 2001
  • This paper describes the application of Fuzzy Logic Controller (FLC) to Thyristor Controlled Series Capacitor (TCSC) which can have significant impact on power system dynamics. The function of the FLC is to control the firing angle of the TCSC. We tuned the scaling factors of the FLC using Tabu Search. The proposed FLC is used for damping the low frequency oscillations caused by disturbances such as the sudden changes of small or large loads or the outages in the generators or transmission lines. To evaluate usefulness of the proposed FLC, we performed the computer simulation fur single-machine infinite system. The response of FLC is compared with that of PD controller optimized using Tabu Search. Simulation results that the FLC shows better control performance than PD controller.

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The Optimal Controller Design of Buck-Boost Converter by using Adaptive Tabu Search Algorithm Based on State-Space Averaging Model

  • Pakdeeto, Jakkrit;Chanpittayagit, Rangsan;Areerak, Kongpan;Areerak, Kongpol
    • Journal of Electrical Engineering and Technology
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    • 제12권3호
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    • pp.1146-1155
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    • 2017
  • Normally, the artificial intelligence algorithms are widely applied to the optimal controller design. Then, it is expected that the best output performance is achieved. Unfortunately, when resulting controller parameters are implemented by using the practical devices, the output performance cannot be the best as expected. Therefore, the paper presents the optimal controller design using the combination between the state-space averaging model and the adaptive Tabu search algorithm with the new criteria as two penalty conditions to handle the mentioned problem. The buck-boost converter regulated by the cascade PI controllers is used as the example power system. The results show that the output performance is better than those from the conventional design method for both input and load variations. Moreover, it is confirmed that the reported controllers can be implemented using the realistic devices without the limitation and the stable operation is also guaranteed. The results are also validated by the simulation using the topology model of MATLAB and also experimentally verified by the testing rig.

Optimal PID Controller Design for DC Motor Speed Control System with Tracking and Regulating Constrained Optimization via Cuckoo Search

  • Puangdownreong, Deacha
    • Journal of Electrical Engineering and Technology
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    • 제13권1호
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    • pp.460-467
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    • 2018
  • Metaheuristic optimization approach has become the new framework for control synthesis. The main purposes of the control design are command (input) tracking and load (disturbance) regulating. This article proposes an optimal proportional-integral-derivative (PID) controller design for the DC motor speed control system with tracking and regulating constrained optimization by using the cuckoo search (CS), one of the most efficient population-based metaheuristic optimization techniques. The sum-squared error between the referent input and the controlled output is set as the objective function to be minimized. The rise time, the maximum overshoot, settling time and steady-state error are set as inequality constraints for tracking purpose, while the regulating time and the maximum overshoot of load regulation are set as inequality constraints for regulating purpose. Results obtained by the CS will be compared with those obtained by the conventional design method named Ziegler-Nichols (Z-N) tuning rules. From simulation results, it was found that the Z-N provides an impractical PID controller with very high gains, whereas the CS gives an optimal PID controller for DC motor speed control system satisfying the preset tracking and regulating constraints. In addition, the simulation results are confirmed by the experimental ones from the DC motor speed control system developed by analog technology.

A Fuzzy Logic Controller for Speed Control of a DC Series Motor Using an Adaptive Evolutionary Computation

  • Hwang, Gi-Hyun;Hwang, Hyun-Joon;Kim, Dong-Wan;Park, June-Ho
    • Transactions on Control, Automation and Systems Engineering
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    • 제2권1호
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    • pp.13-18
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    • 2000
  • In this paper, an Adaptive Evolutionary Computation(AEC) is proposed. AEC uses a genetic algorithm(GA) and an evolution strategy (ES) in an adaptive manner is order to take merits of two different evolutionary computations: global search capability of GA and local search capability of ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. AEC is used to design the membership functions and the scaling factors of fuzzy logic controller (FLC). To evaluate the performances of the proposed FLC, we make an experiment on FLC for the speed control of an actual DC series motor system with nonlinear characteristics. Experimental results show that the proposed controller has better performance than that of PD controller.

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Sensorless Vector Control for Induction Motor Drive using Modified Tabu Search Algorithm

  • Lee, Yang-Woo;Kim, Dong-Wook;Lee, Su-Myoung;Park, Kyung-Hun
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.377-381
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    • 2003
  • The design of speed controller for induction motor using tabu search is studied. The proposed sensorless vector control for Induction Motor is composed of two parts. The first part is for optimizing the initial parameters of input-output. The second part is for real time changing parameters of input-output using tabu search. Proposed tabu search is improved by neighbor solution creation using Gaussian random distribution. In order to show the usefulness of the proposed method, we apply the proposed controller to the sensorless speed control of an actual AC induction Motor System. The performance of this approach is verified through simulation.

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