• Title/Summary/Keyword: Error-immune

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Intelligent Tuning of PID Controller With Disturbance RejectionUsing Immune Algorithm

  • Kim, Dong-Hwa;Cho, Jae-Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.885-890
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    • 2004
  • Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the reheater. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the Controller with disturbance rejection for thermal power plant using immune based multiobjective approach. An ITSE(Integral of time weighted squared error) is used to decide performance of tuning results.

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A Fuzzy Controller Using Artificial Immune Algorithm for Trajectory Tracking of WMR (경로 추적을 위한 구륜 이동 로봇의 인공 면역 알고리즘을 이용한 퍼지 제어기)

  • Kim Sang-Won;Park Chong-Kug
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.6
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    • pp.561-567
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    • 2006
  • This paper deals with a fuzzy controller using IA(Immune Algorithm) for Trajectory Tracking of 2-DOF WMR(Wheeled Mobile Robot). The global inputs to the WMR are reference position and reference velocity, which are time variables. The global output of WMR is a current position. The tracking controller makes position error to be converged 0. In order to reduce position error, a compensation velocities on the track of trajectory is necessary. Therefore, a FIAC(Fuzzy-IA controller) is proposed to give velocity compensation in this system. Input variables of fuzzy part are position errors in every sampling time. The output values of fuzzy part are compensation velocities. IA are implemented to adjust the scaling factor of fuzzy part. The computer simulation is performed to get the result of trajectory tracking and to prove efficiency of proposed controller.

Auto-Tuning Of Reference Model Based PID Controller Using Immune Algorithm

  • Kim, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.102.5-102
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    • 2002
  • In this paper auto-tuning scheme of PID controller based on the reference model has been studied by immune algorithm for a process. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Simulation results by immune based tuning reveal that tuning approaches suggested in this paper is an effective approach to search for optimal or near optimal process control.

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Adaptive Intelligent Control of Inverted Pendulum Using Immune Fuzzy Fusion

  • Kim, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2372-2377
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    • 2003
  • Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,{\dot{x}},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

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Intelligent 2-DOF PID Control For Thermal Power Plant Using Immune Based Multiobjective

  • Kim, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1371-1376
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    • 2003
  • In the thermal power plant, the main steam temperature is typically regulated by the fuel flow rate and the spray flow rate, and the reheater steam temperature is regulated by the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature, the change of the dynamic characteristics in the reheater. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. This paper focuses on tuning of the 2-DOF PID Controller on the DCS for steam temperature control using immune based multiobjective approach. The stable range of a 2-DOF parameter for only this system could be found for the start-up procedure and this parameter could be used for the tuning problem. Therefore tuning technique of multiobjective based on immune network algorithms in this paper can be used effectively in tuning 2-DOF PID controllers.

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Intelligent Control of Power Plant Using Immune Algorithm Based Multiobjective Fuzzy Optimization

  • Kim, Dong-Hwa
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.525-530
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    • 2003
  • This paper focuses on design of nonlinear power plant controller using immune based multiobjective fuzzy approach. The thermal power plant is typically regulated by the fuel flow rate, the spray flow rate, and the gas recirculation flow rate. However, Strictly maintaining the steam temperature can be difficult due to heating value variation to the fuel source, time delay changes in the main steam temperature. the change of the dynamic characteristics in the steam-turbine system. Up to the present time, PID Controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error. These parameters tuned by multiobjective based on immune network algorithms could be used for the tuning of nonlinear power plant.

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Intelligent Control of Nonlinear dynamic system Using Immune Fuzzy Fusion

  • Kim, Dong-Hwa
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.1
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    • pp.70-78
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    • 2004
  • This paper proposes non-linear control method using immune algorithm based fuzzy logic. Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because gain of the PID controller has to be manually tuned by trial and error. An inverted pendulum control problem is selected to illustrate the efficiency of the proposed method and defines relationship state variables $\chi$, $\chi$, $\theta$, $\theta$ using immune fuzzy.

Adaptive Intelligent Control of Nonlinear dynamic system Using Immune Fuzzy Fusion

  • Kim, Dong-Hwa;Park, Jin-Ill
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.146-156
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    • 2003
  • Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,\dot{x},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

Multiobjective PI Controller Tuning of Multivariable Boiler Control System Using Immune Algorithm

  • Kim, Dong-Hwa;Park, Jin-Ill
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.1
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    • pp.78-86
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    • 2003
  • Multivariable control system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, Pill Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the Pill controller has to be manually tuned by trial and error. This paper suggests a tuning method of the Pill Controller for the multivariable power plant using an immune algorithm, through computer simulation. Tuning results by immune algorithms based neural network are compared with the results of genetic algorithm.

A Study on Steering Performance Improvement of the AGV using Cell-Mediated Immune Algorithm (세포성 면역 알고리즘을 이용한 AGV의 조향 성능 향상에 관한 연구)

  • Lee, Y.J.;Sohn, J.H.;Lee, J.W.;Cho, H.C.;Lee, K.S.
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2572-2574
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    • 2000
  • In this paper, cell-mediated immune algorithm(CMIA) controller was proposed and applied for the autonomous guided vehicle(AGV) driving. It was based on specific immune response of the biological immune system which is the cell-mediated immunity. To verify the performance of the designed CMIA controller, some experiments were performed for the control of steering and speed of AGV. And then the displacement and speed tracking error of the AGV was mainly investigated. As results, the capability of realization and reliableness were proved by comparing the response characteristics of the classical controller with the proposed CMIA controller.

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