• 한국항만학회지
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• 제14권2호
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• pp.187-197
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• 2000

In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied to the driving control of the autonomous guided vehicle(AGV). When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged by the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined through this off-line manner, these parameters 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 initially, the weighting parameters are adjusted more accurately through the on-line fine tuning. The experiment for the control of steering and speed of AGV is performed. The results show that the proposed controller provides better performances than other conventional controllers.

• 제어로봇시스템학회논문지
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• 제10권12호
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• pp.1137-1147
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• 2004

In this paper, we proposed two types of adaptive control mechanism which is named HIA(Humoral Immune Algorithm) PID and CMIA(Cell-Mediated Immune Algorithm) controller based on biological immune system under engineering point of view. The HIA PID which has real time control scheme is focused on the humoral immunity and the latter which has the self-tuning mechanism is focused on the T-cell regulated immune response. To verify the performance of the proposed controller, some experiments for the control of AGV which is used for the port automation to carry container without human are performed. The experimental results for the control of steering and speed of an AGV system illustrate the effectiveness of the proposed control scheme. Moreover, in that results, proposed controllers have better performance than other conventional PID controller and intelligent control method which is the NN(neural network) PID controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 추계학술대회 논문집 학회본부
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• pp.370-372
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• 1994

In this paper, a stable adaptive composite control system consisting of a PID and a fuzzy controllers is designed to control nonlinear systems. In the fuzzy controller, parameters of membership functions characterizing the linguistic terms change according to some adaptive law. Also, parameters of PID controller change according to some adaptive law. These adaptive laws are based on the Lyapunov synthesis approach. Then, it is proved that the closed-loop system using such an adaptive composite control system is globally stable in the sense that all signals involved are bounded and the tracking error converges to zero. We apply this adaptive composite control system to control a nonlinear system.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2005년도 춘계종합학술대회
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• pp.289-292
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• 2005

각종 산업기기에서 사용되는 PID 제어기는 단순한 구조와 모델링 오차에 대한 강인성으로 인하여 광범위하게 사용되고 있다. 그러나 외란이 인가되거나 부하 특성이 비선형적으로 변화할 때에 적절한 이득과 성능을 얻기 어려워 고성능 제어 특성을 기대하기 어렵다. 본 연구에서는 구조가 간단하고, 시스템 파라메터의 변화에 강인한 적응 PID 제어기를 제안한다. 제안된 적응 PID제어기의 성능 평가를 위하여 비선형 DC 모터의 가변 속도제어에 적용하고, 결과를 모의실험을 통하여 보이고자한다.

• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.609-615
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• 2007

We propose an optimized adaptive PID control scheme. This paper is focused on the development of model reduction as well as a new adoptive control structure (viz. a recursive least square estimation (RLSE) method-based structure) that is constructed with smith-predictor structure and a real time estimator. The estimator adjust parameters of a reduced model in real time. It leads to robust and superb control performance for the noise or variation of parameters of process. Experimental study reveals that the proposed control structure exhibits more superb output performance in comparison to some previous methods.

• 동력기계공학회지
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• 제9권4호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.913-916
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• 1988

Indirect adaptive pole assignment PID controllers for unknown systems with time varying delay, is proposed. Unknown system parameters are estimated by recursive least square method, and time varying delay is estimated using indirect predictors. Since the order of parameter vectors didn't increase, the computational burden is not largely increased in spite of using indirect adaptive control method with time varying delay estimation. Computer simulation is performed to illustrate the efficiency of the proposed method.

• 제어로봇시스템학회논문지
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• 제4권2호
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• pp.209-214
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• 1998

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.

• 센서학회지
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• 제19권5호
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• pp.375-384
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• 2010

In this paper, we proposed a new shaft distortion correction system having an adaptive PID controller using displacement sensors, which is adaptively reflecting variations of shaft strength owing to irregular heat treatment during an annealing process and sensitivity to the seasonal temperature changes. Generally, the shafts are annealed by heat treatment in order to enlarge the strength of the shaft, which causes an distortion of a shaft such as irregular bending of the shaft. In order to correct such a distortion of the shaft, a mechanical pressure is properly impacted to the distorted shaft. However, the strength of every shaft is different from each other owing to irregular annealing and seasonal temperature changes. Especially, the strength of a thin shaft such as a car transmission shaft is much more sensitive than that of a thick shaft. Therefore, it is very important for considering the strength of each shaft during correction of the car transmission shaft distortion in order to generate proper mechanical pressure. The conventional PID controller for the shaft distortion correction system does not consider each different strength of each shaft, which causes low productivity. Therefore, we proposed a new PID controller considering variations of shaft strength caused by seasonal temperature changes as well as irregular heat treatment and different cooling time. Three displacement sensors are used to measure a degree of distortion of the shaft at three different location. The proposed PID controller generates adaptively different coefficients according to different strength of each shaft using appropriately obtained pressure times from long-term experiments. Consequently, the proposed shaft distortion correction system increases the productivity about 30 % more than the conventional correction system in the real factory.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2345-2348
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• 2003

This paper deals with a problem of automatic landing guidance and control system design. The auto-landing control system for the longitudinal motion is designed in the classical PID controller. The controller gains are properly adapted to variation of the performance using fuzzy logic as a gain scheduler for the PID gains. This control logic is applied to the problem of the automatic landing control system design. From the numerical simulation using the 6DOF nonlinear model of the associated airplane, it is shown that the auto-landing maneuver is successfully achieved from the start of the flight conditions: 1500 ft altitude, 250 ft/sec airspeed and zero flight path angle.