• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.128.4-128
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• 2001

Based on fuzzy logic algorithm this paper constructed fuzzy logic controller for automated vehicles. For passenger´s convenience especially comfortability controller need to reduce the frequency of input variable´s changing. So we established membership functions for comfortability as well as speed following. It made possible to control comfortability directly. To demonstration the efficiency of fuzzy logic controller, we carried out simulation with a automobile´s transfer function. First, we designed the PID controller by using Ziegler-Nichols tunning method. Second, we calculated time response for each controller, then we compared the speed patterns of fuzzy controlled system and PID controlled system. Also we compared the difference of input variable ...

• 연구논문집
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• s.23
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• pp.73-80
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• 1993

This study presents an intelligent PID control method based on the fuzzy logic and this method is applied to the active magnetic bearing system. By using an appropriate fuzzy matrix, some changes of values of the three coefficients of the controller are determined during system operation and these lead to the improvement of the transient and steady state behavior of the closed loop system. The presented method is actually a combination of the principles of PID control and fuzzy logic. Since the fuzzy logic using linguistic variables in place of numeric variables has many points of likeness to the human logic, the improvement in performance is notable especially in case of large nonlinearity and uncertainty such as the controller start and the excessive mass unbalance. A set of simulation and experimental results illustrate and considerable improvement in the control performance including small overshoot and small transient currents in magnet coils, while maintaining the overal static and dynamic characteristics near the equilibrium position.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.345-348
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• 1991

This paper describes a new auto tuning method for the intelligent PID control system. This new method is hosed on the settling time of the process and has been introduced into auto-tuning PID controller using fuzzy logic. The performance of the controller is measured by computer simulation. Simulation shows good results that controller searches well the optimal values of PID parameters in any conditions and the response characteristic of the control system is improved.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.240-243
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• 2001

A conventional PID controller does not provide a proper response in face of various kinds of load variation. In this paper, Fuzzy-PID Control scheme are proposed in order to improve the performance of the PID Controller. The proposed control schemes are applied to the speed controller of AC servo motor systems. The effectiveness of the proposed methods is shown by implementation and the advantage of each control scheme is discussed.

• Journal of the Korean Institute of Navigation
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• v.24 no.3
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• pp.141-145
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• 2000

In servo-system which need fast response and accuracy, PID controller has a good steady-state performance, but has a poor transient response performance causing a load be changed. Compared to these features, FLC(Fuzzy Logic Controller) has a good transient response performance for changed load, but has a little Poor steady-state performance. In this paper, Compensated Fuzay Controller which consists of PID controller and FLC is proposed to modify these disadvantages and is examined through simulation to evaluate its functions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.342-345
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• 2003

This paper presents an adaptive PID control scheme for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model is used to estimate the error of control input, and the parameter of PID controller are adapted using the error. The parameters of TSK fuzzy model are also adapted to plant. The proposed algorithm allows designing adaptive PID controller which is adapted to the uncertainty of nonlinear plant and the change of parameters. The usefulness of the proposed algorithm is also certificated by the several simulations.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.700-702
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. In fuzzy controller which has been widely applied and used. in order to construct the best fuzzy rules that include adjustment of fuzzy sets, a highly skilled techniques using trial and error are required. To deal with such a problem, first, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller from each control output in steady state and transient state. Second, a auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller, utilizing the simplified reasoning method and genetic algorithms. In addition, to obtain scaling factors and PID Parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The HFCs are applied to the first-order second-order process with time-delay and DC motor Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed from performance indices.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.30-41
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• 2004

This paper is concerned with the active vibration control of flexible cantilever beam system using electromagnetic farce actuator. The main objective of this paper is to propose the control algorithms and to implement the experimental setups for active vibration control. Dynamic equations of the electromagnetic actuator and the beam are combined to find the transfer function from the electromagnetic actuator to the laser sensor. The final transfer function is determined by considering only the first and second modes, and experiments confirm that this model works well. Several control algorithms are proposed and implemented on the experimental setups to show their efficacy. These include a PID control design, an optimal H$_2$ control design, and a fuzzy PID control design. Effectiveness and performance of the designed controller were verified by both simulation and experiment results.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.678-680
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• 1998

Based on fuzzy logic algorithm this paper constructed fuzzy logic controller for automated vehicles. For passenger's convenience especially comfortability controller need to reduce the frequency of input variable's changing. So we established membership functions for comfortability as mil as speed following. It made possible to control comfortability directly. To demonstration the efficiency of fuzzy logic controller, we carried out simulation with a Automobile's transfer function. First, we designed the PID controller by using Ziegler-Nichols tunning method. Second, we calculated time response for each controller, then we compared the speed patterns of fuzzy controlled system and PID controlled system. Also we compared the difference of input variable. By comparing two controller's response, we can confirm the merit of fuzzy controller about comfortability. Fuzzy controller can reduce input changing frequency.

• Journal of Navigation and Port Research
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• v.35 no.5
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• pp.359-363
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• 2011

In this paper, automatic control system for the Manta UUV are constructed for the diving and steering maneuver. PID controller and Fuzzy controller are adopted in this system. Based on the 6DOF dynamic equation, simulation program has been developed using the Matlab. Using this program, depth control system and heading control system with tidal current are evaluated.