• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.144-147
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• 2006

A proportional intergral (PI) control strategy is commonly used for constant current and extinction angle control in a HVDC (High Voltage Direct Current) system. A PI control strategy is based on a stactic design where the gains of a PI controller are fixed. Since the response of a HVDC plant dynamically changes with variations in the operation point a PI controller performance is far from optimum. The contribution of this paper is the presentation of the design of a rough set based, fuzzy adaptive control scheme. Experimental results that compare the performance of the adaptive control and PI control schemes are also given.

• 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.

• 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...

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.4
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• pp.73-81
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• 2003

DC series wound motor is commonly used for the industrial vehicles. Although it has good operating torque, heavy variations of parameters and nonlinear properties on friction and loads make it difficult to satisfy desired performance using conventional controllers. To solve this problem, fuzzy controller is proposed in this paper. The fuzzy controller has been designed based on the fuzziness of variables, it retains robustness even with nonlinearity.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.70-70
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• 2000

Recently, a neuro-fuzzy approach, a combination of neural networks and fuzzy reasoning, has been playing an important role in the motor control. In this paper, a novel method of fiction compensation using neuro-fuzzy architecture has been shown to significantly improve the performance of a DC motor system with nonlinear friction characteristics. The structure of the controller is the neuro-fuzzy network with the TS(Takagi-Sugeno) model. A back-propagation neural network based on a gradient descent algorithm is employed, and all of its parameters can be on-line trained. The performance of the proposed controller is compared with both a conventional neuro-controller and a PI controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.10
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• pp.443-445
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• 2006

Generally PI controller is used to control the speed of an induction motor. It has the good performance of speed control in case of adjusting the control parameters. But it occurred the problem to change the control parameters in the change of operation condition. In order to solve this problem, Fuzzy control or Artificial neural network is introduced in the speed control of an induction motor. However, Fuzzy control have the problems as the difficulties to change the membership function and fuzzy rule and the remaining error Also Neural network has the problem as the difficulties to analyze the behavior of inner part. Therefore, the study on the combination of two controller is proceeded. In this paper, Fuzzy-neural controller to make up these controllers in parallel is proposed and the speed control of an induction motor is performed using the proposed controller Through the experiment, the fast response and good stability of the proposed speed controller is proved.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.1
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• pp.111-121
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• 1995

A fuzzy control algorithm of bell-type membership functions and 9 rules is constructed for narrow range level control of steam generators in nuclear power plants. It is implemented at a field digital distributed controller, a Westinghouse-made controller called Westinghouse Distributed Processing Family(WDPF). Performance for level control of the developed fuzzy controller is compared with that of conventional controller, both at the field controller. For these comparisons, both the fuzzy control algorithm and the conventional PI control algorithm were carefully tuned. Also the sampling time for optimal performance was investigated. The results show that the fuzzy control algorithm is not only better in performance than the conventional algorithm but also much easier to be tuned by operators in the field.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2001.05a
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• pp.238-242
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• 2001

In this paper, we proposed an optimal identification method of the membership functions and the numbers of fuzzy rule base for the stabilization controller of the Thermal process control system by RVEGA. Although fuzzy logic controllers and expert systems have been successfully applied in many complex industrial process, they must rely on experts knowledges. So it is difficult in determination of the linguistic state space, definition of the membership functions of each linguistic term and the derivation of the control rules. To verify the validity of this RVEGA-based fuzzy controller, Thermal process control system, with strong nonlinear dynamics, was selected for application of this algorithm and compare with PI controller, and the empirically improved fuzzy controller.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.31-41
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• 1993

In this paper, a fuzzy adaptive controller is proposed for the process with large delay time and unmodelled dynamics. The fuzzy adaptive controller consists of self tuning controller and fuzzy tuning part. The self tuning controller is designed with the continuous time GMV (generalized minimum variance) using emulator and weighted least square method. It is realized by the hybrid method. The controller has robust characteristics by adapting the inference rule in design parameters. The inference processing is tuned according to the operating point of the process having the nonlinear characteristics considering the practical application. We review the characteristics of the fuzzy adaptive controller through the simulation. The controller is applied to practical electric furnace. As a result, the fuzzy adaptive controller shows the better characteristics than the simple numeric self tuning controller and the PI controller.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.8 no.1
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• pp.46-52
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• 1994

In this paper, we implemented the variable speed controller of an induction motor by the Fuzzy control algorithms, which recently is invoking the remarkable interest. As the fuzzy controller is designed on the base of expert's knowlede and experience, it is difficult to expect the perfect control performance of fuzzy controller. Therefore, the adjustment techniques for optimization of scale factors were presented to design the robust fuzzy controller comparing with conventional PI control the usefullness of proposed fuzzy controller was showed by the experimental results.