• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2756-2759
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• 2000

In this paper. A PID motion controller based on the fuzzy concept is discussed for nonholonomic mobile robot. The difficulties in controlling such a Mobile robot vehicle lies in the fact that it usually has only two degrees of freedom for motion control in a tracking mode. It makes the control of speed and steering possible to decompose the error between the reference posture and the current posture. The Gyro compass is used to measure the position of robot. The proposed nonholonomic mobile robot is shown to follow the reference trajectory and compensate the dynamics. Simulation results are provided to validate the proposed controller. Experiments have been used to verify the effectiveness and robustness of the motion controller.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2386-2388
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• 2000

This paper proposes a novel method with pseudo-on-line scheme using look-up table based on the genetic algorithm. The technique is a pseudo-on-line method that optimally estimate the parameters of fuzzy PID(FPID) controller for systems with non-linearity using the genetic algorithm which does not use the gradient and finds the global optimum of an un-constraint optimization problem. The proposed controller(GFPID) is applied to speed control of 3-phase induction motor and its computer simulation is carried out. Simulation results show that the proposed method is more excellent than conventional FPID and PID controllers.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2470-2472
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• 2000

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.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.777-780
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• 1999

In this paper, a fuzzy logic controller is designed for speed control of a hydraulic inverter elevator. Mathematical modeling of an elevator actuated with hydraulic system is presented and the friction characteristics of a cylinder is examined, which may cause the abrupt increase of the acceleration in the zero-crossing speed region. Simulation results show that the proposed fuzzy logic speed controller yields a better control performance than conventional PID controller.

• Journal of Industrial Technology
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• v.16
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• pp.231-237
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• 1996

In this paper, the nonlinear I/O characteristic of fuzzy logic controller is analyzed by using cell concept. Sources of the nonlinearity in a fuzzy logic controller include the fuzzification, the fuzzy reasoning and the defuzzification. A closed form expression for the defuzzified output is derived in case of a fuzzy logic controller with two inputs, triangular memberships, MacVicar-Whelan type linguistic rules, and direct fuzzy reasoning. As a result, it is shown that fuzzy logic controller is a nonlinear controller. Also its nonlinearity is analyzed with respect to the conventional PID control and the sliding mode control.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.129-134
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• 1992

Fuzzy theory has shown good control performance for non-linear system that is difficult to be controlled by the conventional controller. Backpropagation neural network can interpolate output without the priori knowledge of its dynamics. In this paper, we proposes a Fuzzy-Neural Controller. The Fuzzy Control by deterministic rule may not be sensitive for uncertain conditions and has a disadvantage of setting the rule by repeatedly experience. To solve such problems, we construct Self organizing Fuzzy-Neural Controller which can reorganize the fuzzy rule according to the state of system. Experimental results show that proposed Fuzzy-Neural Controller has better performance than conventional controller(PID) has especially rising time and overshoot characteristics.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.717-719
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• 1995

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy controller and propose the tuning method for them. The quantitative relation between input and output variables of a fuzzy controller is obtained by using a quasi-linear fuzzy model. An approximate transfer function of a fuzzy controller is derived from the comparison a fuzzy controller with the conventional PID controller. We analyze the effects of scaling factor using this approximate transfer function and propose a fuzzy tuning method based on that of Maeda et al[4].

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.233-233
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• 2000

Direct torque control (DTC) scheme provides a very quick torque response without the complex field-orientation block and inner current regulation loop. DTC is known as an appropriate scheme for high power induction motet drives because it can be used at lower switching frequency. There are two major drawbacks with the application of DTC schemes : one is large current harmonics due to flux drooping in a low speed range, the other is that the inverter switching frequency is varying according to motor parameters and operating speed. Switching devices in the power electronics drives should be supported for relatively high switching frequency. In this paper, a P-type fuzzy controller to realize the variable switching sector scheme and a PID-type fuzzy switching frequency regulator are adopted. A meaningful contribution of this paper is to propose a simple realization scheme of the fuzzy switching frequency regulator. Simulation results show the effectiveness of those propositions.

• Journal of the Korea Convergence Society
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• v.4 no.2
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• pp.43-50
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• 2013

Sliding mode control(SMC) are carried out in this literature. And to make the controllers perform better, fuzzy logic was chosen,it makes PID controller auto-tuning parameters and reduced the chattering problem of sliding mode control. Since SMC take error and derivative of error as inputs, after comparison some results are obtained.PID controller response faster yet sliding mode control is much steadier. However certain problems cannot be ignored that the chattering phenomenal cannot be reduced entirely and this motion may hurt the machine; this project only considered a simple system, there is no guarantee PID can work as well as in this case for a much more complex system. MATLAB simulink was the main approach to obtain the performance of the two controllers: to observe the control output of the two controllers, electric circuit and special controllers are designed and tested in MATLAB.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.3
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• pp.320-327
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• 1998

The purpose of this study is to design the intelligent speed control system for marine diesel engine by combining the Model Matching Method and the Nominal Model Tracking Method. Recently for the speed control of a diesel engine some methods using the advanced control techniques such as LQ control Fuzzy control or H$\infty$ control etc. have been reported. However most of speed controllers of a marine diesel engine developed are still using the PID control algorithm But the performance of a marine diesel engine depends highly on the parameter setting of the PID controllers. The authors proposed already a new method to tune efficiently the PID parameters by the Model Mathcing Method typically taking a marine diesel engine as a non-oscillatory second-order system. It was confirmed that the previously proposed method is superior to Ziegler & Nichols's method through simulations under the assumption that the parameters of a diesel engine are exactly known. But actually it is very difficult to find out the exact model of the diesel engine. Therefore when the model and the actual diesel engine are unmatched as an alternative to enhance the speed control characteristics this paper proposes a Model Refernce Adaptive Speed Control system of a diesel engine in which PID control system for the model of a diesel engine is adopted as the nominal model and a Fuzzy controller is adopted as the adaptive controller, And in the nominal model parameters of a diesel engine are adjusted using the Model Matching Method. it is confirmed that the proposed method gives better performance than the case of using only Model Matching Method through the analysis of the characteristics of indicial responses.