• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.622-631
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• 2001

This paper presents a fuzzy modified PID controller that uses linear fuzzy inference method. In this structure, the proportional and derivative gains vary with the output of the system under control. 2-input PD type fuzzy controller is designed to obtain the varying gains. The proposed fuzzy PID structure maintains the same performance as the same performance as the general-purpose linear PID controller, and enhances the tracking performance over a wide range of input. Numerical simulations and experimental results show the effectiveness of the fuzzy PID controller in comparison with the conventional PID controller.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.732-735
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• 2007

Recently the control of induction motor for position control has been extensively studied. The representative method is PIDA controller proposed by Jung&Dorf. By designed PIDA controller' parameter had large value. Moreover, this method is very analyze, so that, not adapted controller parameter in disturbance. Besides using generalize fuzzy controller. Because input and output membership function is linguistic type, therefore system response is very slow. So, in this paper we used optimized fuzzy controller. Optimized fuzzy controller is output membership function is unity value. The controller performance was estimated applied to induction motor' position control.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.6
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• pp.760-769
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• 2006

This paper proposes an autopilot system using a fuzzy PID controller to satisfy performances required for the automatic navigation of ships under various marine circumstances. The existing autopilot system using a PD type controller has difficulties in eliminating a steady-state error and compensating nonlinear characteristics of ships. The autopilot system using the proposed fuzzy PID controller has a self-tuning ability, an ability to compensate nonlinear characteristics, and an ability to turn at constant angular velocity. Therefore. it can naturally make a steady-state error zero, compensate nonlinear dynamic effect of ships, have an adaptability to parameter variation owing to shallow water effect, and have an ability to turn ship's course rapidly without overshoot through procedures of acceleration, constant, and deceleration of angular velocity for large course-changing.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.101.4-101
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• 2002

I. Introduction ▶The PID(Proportional-Integral-Derivative) controller is widely used in the industry it can be implemented easily for a typical second order plant. ▶The parameters of PID controller should be adapted complicatedly if a plant is various or the load is present. ▶For solving the problem, many control techniques have been developed. ▶A major method is a hybrid Fuzzy-PID controller. But, in case of using this method, we can not obtain characteristic of rapidly response and not achieved compensation on disturbance. ▶Therefore, we will use compensator fuzzy controller a front Hybrid type fuzzy-PID controller...

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.8
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• pp.352-359
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• 2002

A neuro-fuzzy controller has some problems that he difficulty of tuning up the membership function and fuzzy rules, long time of inferencing and defuzzifying compare to PID. Also, the fuzzy controller's own defect as a PD controller has. In this study, it is proposed two methods to solve these problems. The first method is that inner fuzzy rules are tuned up automatically by the back propagation learning according to error patterns. And the second method is a new type defuzzification method that shorten the calculation time of an inferencing and a defuzzifying. In this study, it is designed the new type neuro-fuzzy controller that improves the fast response and the stability of a system by using the proposed methods. And, the designed controller is named EPLNFC(Error pattern Learning Neuro-Fuzzy Controller). To evaluate the fast response and the stability of EPLNFC designed in this study, EPLNFC is applied to a speed control of a DC motor and AC motor.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.150-159
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• 2010

The approach and landing phase of a re-entry vehicle is composed of Steep Glideslope phase, Circular Flare phase, Flare Maneuver phase. The trajectory planning algorithm with geometric parameters is studied in this paper for on-board trajectory planning. This algorithm generate reference trajectory rapidly considering safe landing of re-entry vehicle. In this paper, the Mamdani Fuzzy PD type controller for longitudinal and lateral control is designed which has robustness of nonlinear system. In addition, the simulation is performed including initial downrange and crossrange errors, and the results shows that the proposed fuzzy logic controller has good performance.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.260-265
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• 1995

Based on a thermohydraulic estimation of the level swell and shrinkage of the nuclear steam generators, a fuzzy logic controller is designed and tested to handle the problem of controlling the level swell and its restoration. The estimation is used to form an artificial system which is nearly the opposite of the level swell and shrinkage and a PD type controller is designed to control this system. This controller is added to a PI type ordinary fuzzy logic controller to form the proposed controller which is tested through various experiments on a scaled-down steam generator. It is found to perform efficiently so that the divergence of the level to a low limit can be avoided.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.155-162
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance, FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and to increase efficiency. a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy PI and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and the resultant rule base is Macvicar-Whelan type. And the membership function is a Gaussian function. The frequency response information is used in tuning of the membership functions. Also a tuning strategy for the scaling factors is proposed based on the relationship between PID gain and the scaling factors. Simulation results show better performance and the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.360-363
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• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of rules from human operator. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.650-652
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance. FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and increase efficiency, a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy Pi and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and them. The resultant rule base is Macvicar-Whelan type. The frequency response information is used in tuning of membership functions. Also a tuning strategy for the scaling factors is Proposed based on the relationship between PID gain and them. Simulation results show better performance and the effectiveness of the proposed method.