• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.91.5-91
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• 2001

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes accord Eng to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems ...

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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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.

• 한국지능시스템학회논문지
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• 제12권3호
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• pp.246-254
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• 2002

In this paper auto-tuning scheme of PID controller based on the reference model has been studied for a Process control system by immune algorithm. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. Also, a number of approaches have been proposed to implement mixed control structures that combine a PID controller with fuzzy logic. 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. Since the immune system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (Parallel Distributed Processing) network to complete patterns against the environmental situation. Simulation results reveal that reference model basd tuning by immune network suggested in this paper is an effective approach to search for optimal or near optimal process control.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권9호
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• pp.402-412
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• 2002

The navigation algorithms enable autonomous mobile robots to reach given target points without collision against obstacles. To achieve safe navigations in unknown environments, this paper presents an effective navigation algorithm for the autonomous mobile robots with ultrasonic sensors. The proposed navigation algorithm consists of an obstacle-avoidance behavior, a target-reaching behavior and a fuzzy-based decision maker. In the obstacle-avoidance behavior and the target-reaching behavior, artificial immune networks are used to select a proper steering angle, make the autonomous mobile robot avoid obstacles and approach a given target point. The fuzzy-based decision maker combines the steering angles from the target-reaching behavior and the obstacle-avoidance behavior in order to steer the autonomous mobile robot appropriately. Simulational and experimental results show that the proposed navigation algorithm is very effective in unknown environments.

• Journal of Advanced Marine Engineering and Technology
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• 제26권4호
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• pp.415-424
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• 2002

In this paper, a robust fuzzy precompensated PID controller using immune algorithm for load frequency control of 2-area power system is proposed. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic based precompensation approach for PID controller. This scheme is easily implemented by adding a fuzzy precompensator to an existing PID controller. We optimize the fuzzy precompensator with an immune algorithm for complementing the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and fuzzy rules. Simulation results show that the proposed robust load frequency controller can achieve good performance even in the presence of generation rate constraints.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.185-188
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• 2001

According as many people use a computer newly, damage of computer virus and hacking is rapidly increasing by the crucial users. To block hacking that is intrusion of a person's computer and the computer virus that destroys data, a study for intrusion-detection of system and virus detection using a biological immune system is in progress. In this paper, we make a model of positive selection and negative selection of self-recognition process that is ability of T-cytotoxic cell that plays an important part in biological immune system. So we embody a self-nonself distinction algorithm in computer. To prove the efficacy of self-recognition algorithm, we use simulations by a cell change and a string change of self file.

• 동력기계공학회지
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• 제10권3호
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• pp.88-96
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• 2006

While the crane system operate in port, one of main objective is to transport containers to the goal position as soon as possible. Because this is one of the biggest problem in terms of productivity of port, the container crane is operated by an expert operator until now. However recently an automatic control system with high performance is required to improve the performance of the crane system and to make high productivity. Therefore we developed an optimal controller based on Humoral Immune Algorithm with PID controller. The proposed system has a real time structure and can improve the performance such as anti-sway problem. Some computer simulations are implemented to assess the characteristics of the proposed controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.231-235
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• 2004

According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

• 제어로봇시스템학회논문지
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• 제12권6호
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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.