• 제목/요약/키워드: immune algorithm

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Immune Algorithm Controller Design of DC Motor with parameters variation (DC 모터 파라메터 변동에 대한 면역 알고리즘 제어기 설계)

  • 박진현;전향식;이민중;김현식;최영규
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.175-178
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    • 2002
  • The proposed immune algorithm has an uncomplicated structure and memory-cell mechanism as the optimization algorithm which imitates the principle of humoral immune response, and has been used as methods to solve parameter optimization problems. Up to now, the applications of immune algorithm have been optimization problems with non-varying system parameters. Therefore, the effect of memory-cell mechanism, which is a merit of immune algorithm, is without. this paper proposes the immune algorithm using a memory-cell mechanism which can be the application of system with nonlinear varying parameters. To verified performance of the proposed immune algorithm, the speed control of nonlinear DC motor are performed. Computer simulation studies show that the proposed immune algorithm has a fast convergence speed and a good control performances under the varying system parameters.

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Optimization of Controller Parameters using A Memory Cell of Immune Algorithm (면역알고리즘의 기억세포를 이용한 제어기 파라메터의 최적화)

  • Park, Jin-Hyeon;Choe, Yeong-Gyu
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.8
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    • pp.344-351
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    • 2002
  • The proposed immune algorithm has an uncomplicated structure and memory-cell mechanism as the optimization algorithm which imitates the principle of humoral immune response. We use the proposed algorithm to solve parameter optimization problems. Up to now, the applications of immune algorithm have been optimization problems with non-varying system parameters. Therefore the usefulness of memory-cell mechanism in immune algorithm is without. This paper proposes the immune algorithm using a memory-cell mechanism which can be the application of system with nonlinear varying parameters. To verified performance of the proposed immune algorithm, the speed control of nonlinear DC motor are performed. The results of Computer simulations represent that the proposed immune algorithm shows a fast convergence speed and a good control performances under the varying system parameters.

On Designing a Robot Manipulator Control System Using Multilayer Neural Network and Immune Algorithm (다층 신경망과 면역 알고리즘을 이용한 로봇 매니퓰레이터 제어 시스템 설계)

  • 서재용;김성현;전홍태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.267-270
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    • 1997
  • As an approach to develope a control system with robustness in changing control environment conditions, this paper will propose a robot manipulator control system using multilayer neural network and immune algorithm. The proposed immune algorithm which has the characteristics of immune system such as distributed and anomaly detection, probabilistic detection, learning and memory, consists of the innate immune algorithm and the adaptive immune algorithm. We will demonstrate the effectiveness of the proposed control system with simulations of a 2-link robot manipulator.

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Immune Algorithm Controller Design of DC Motor with parameters variation (DC 모터 파라메터 변동에 대한 면역 알고리즘 제어기 설계)

  • Park, Jin-Hyun;Jun, Hyang-Sig;Lee, Min-Jung;Kim, Hyun-Sik;Choi, Young-Kiu
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.4
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    • pp.353-360
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    • 2002
  • Methods for automatic tuning of PID controllers have been on of the results of the active research on control. The proposed controller also is auto-tuning of PID controller The proposed immune algorithm has an uncomplicated structure and memory-cell mechanism as the optimization algorithm which imitates the principle of humoral immune response. We use the proposed algorithm to solve optimization of PID controller parameters. Up to now, the applications of immune algorithm have been optimization problems with non-varying system parameters. Therefore the usefulness of memory-cell mechanism in immune algorithm is without. And research of memory-cell mechanism does not give us entire satisfaction. This paper proposes the immune algorithm using a memory-cell mechanism which can be the application of system with nonlinear varying parameters. To verify performance of the proposed immune algorithm, the speed control of nonlinear DC motor are performed. The results of Computer simulations represent that the proposed immune algorithm shows a fast convergence speed and a good control performances under the varying system parameters.

Optimal Control of Induction Motor Using Immune Algorithm Based Fuzzy Neural Network

  • Kim, Dong-Hwa;Cho, Jae-Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • pp.1296-1301
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    • 2004
  • Fuzzy logic, neural network, fuzzy-neural network play an important as the key technology of linguistic modeling for intelligent control and decision making in complex systems. The fuzzy -neural network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes learning approach of fuzzy-neural network by immune algorithm. The proposed learning model is presented in an immune based fuzzy-neural network (FNN) form which can handle linguistic knowledge by immune algorithm. The learning algorithm of an immune based FNN is composed of two phases. The first phase used to find the initial membership functions of the fuzzy neural network model. In the second phase, a new immune algorithm based optimization is proposed for tuning of membership functions and structure of the proposed model.

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A Design of Steering Controller for AGV using Immune Algorithm (면역 알고리즘을 이용한 AGV의 조향 제어기 설계에 관한 연구)

  • Lee, Chang-Hoon;Lee, Jin-Woo;Lee, Young-Jin;Lee, Kwon-Soon
    • Proceedings of the KIEE Conference
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    • pp.2824-2826
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    • 2002
  • Immune system is an evolutionary biological system to protect innumerable foreign materials such as virus, germ cell, and etcetera. Immune algorithm is the modeling of this systems response that has adaptation and reliability when disturbance occur. In this paper, immune algorithm is proposed to control four wheels steering AGV(Automated Guided Vehicle) in container yard. The adaptive immune system is applied to the PID controller. For design the PID controller using immune algorithm, we tune PID parameters by off-line manner, in order to avoid the damage from abrupt control force. Repeatedly, the PID parameters are adjusted to be accurate by on-line fine tuner of immune algorithm. And then the computer simulation result from the viewpoint of yaw rate and lateral displacement are analyzed and compared with result of conventional PID controller.

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A Study on Driving Control of an Autonomous Guided Vehicle Using Humoral Immune Algorithm(HIA) Adaptive Controller (생체면역알고리즘 적응 제어기를 이용한 AGV 주행제어에 관한 연구)

  • Lee, K.S.;Suh, J.H.;Lee, Y.J.
    • Journal of Power System Engineering
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    • v.9 no.4
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    • pp.194-201
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    • 2005
  • In this paper, we propose an adaptive mechanism based on humoral immune algorithm and neural network identifier technique. It is also applied for an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To slove this problem, we use the neural network identifier technique for modeling the plant humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. Finally, the experimental results for control of steering and speed of AGV system illustrate the validity of the proposed control scheme. Also, these results for the proposed method show that it has better performance than other conventional controller design method such as PID controller.

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On Designing a Robust Control System Using Immune Algorithm (면역 알고리즘을 이용한 강건한 제어 시스템 설계)

  • Seo, Jae-Yong;Won, Kyoung-Jae;Kim, Seong-Hyun;Cho, Hyun-Chan;Jeon, Hong-Tae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.6
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    • pp.12-20
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    • 1998
  • As an approach to develope a control system with high robustness in changing control environment conditions, this paper will propose a robust control system, using multilayer neural network and biological immune system. The proposed control system adjusts weights of the multilayer neural network(MNN) with the immune algorithm. This algorithm is made up of two major divisions, the innate immune algorithm as a first line of defence and the adaptive immune algorithm as a barrier of self-adjustment. Using the proposed control system based on immune algorithm, we will work out a design for the controller of a robot manipulator. And we will demonstrate the effectiveness of the control system of robot manipulator with computer simulations.

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A Study on Adaptive Control of AGV using Immune Algorithm (면역알고리즘을 이용한 AGV의 적응제어에 관한 연구)

  • 이영진;최성욱;손주한;이진우;조현철;이권순
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • pp.56-63
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    • 2000
  • Abstract - In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

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An AGV Driving Control using immune Algorithm Adaptive Controller (면역알고리즘 적응 제어기를 이용한 AGV 주행제어에 관한 연구)

  • Lee, Yeong-Jin;Lee, Gwon-Sun;Lee, Jang-Myeong
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.4
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    • pp.201-212
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    • 2000
  • In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the cast that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

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