• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.200-209
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• 2004

The fuzzy control based on $\alpha$-level fuzzy set decomposition. It is known to produce quick response and calculating time of fuzzy inference. This paper derived the embodiment computational algorithm for defuzzification by min-max fuzzy inference and the center of gravity method based on $\alpha$-level fuzzy set decomposition. It is easy to realize the fuzzy controller hardware. based on the calculation formula. In addition. this study proposed a circuit that generates PWM actual signals ranging from fuzzy inference to defuzzification. The fuzzy controller was implemented with mixed analog-digital logic circuit using the computational fuzzy inference algorithm by min-min-max and defuzzification by the center of gravity method. This study confirmed that the fuzzy controller worked satisfactorily when it was applied to the position control of a dc servo system.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.662-665
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• 2001

As the fuzzy control is applied to servo system the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$-level set decomposition of fuzzy sets by quantize $\alpha$-cuts. This method can be easily implemented with analog hardware. The influence of quantization levels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of do servo system. It examined useful with experiment for dc servo system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.90-96
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• 2005

This paper presents hardware scheme of fuzzy inference engine, based on α-level set decomposition of fuzzy sets for fuzzy control of DC servo system. We propose a method which is directly converted to PWM actuating signal by a one body of fuzzy inference and defuzzification. The influence of quantity α-levels on input/output characteristics of fuzzy controller and output response of DC servo system is investigated. It is concluded that quantity α-cut 4 give a sufficient result for fuzzy control performance of DC servo system. The experimental results shows that the proposed hardware method is effective for practical applications of DC servo system.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.5
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• pp.793-800
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• 2004

The purpose of this study is to develope a servo system with faster and more accurate response. This paper describes a method of approximate reasoning for fuzzy control of servo system based on the decomposition of $\alpha$-level fuzzy sets. We propose that fuzzy logic algorithm is a body from fuzzy inference to defuzzificaion cases where the output variable u directly is generated PWM The effectiveness for robust and faster response of the fuzzy control scheme are verified for a variable parameter by comparison with a PID control and fuzzy control A position control of DC servo system with a fuzzy logic controller is demonstrated successfully.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.50-56
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• 2001

As the fuzzy control is applied to servo system, the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$ -level set decomposition of fuzzy sets by quantize $\alpha$ -cuts. This method can be easily implemented with analog hardware. The influence of quantization Bevels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of dc servo system. The hardware implementation of proposed operation method and of the defuzzification by gravity center method which is directly converted to PWM actuating signal is also presented. It is verified useful with experiment for dc servo system.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.38-40
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• 2000

In this paper we propose a calculation method for fuzzy control based on quantized $\alpha$-cut decomposition of fuzzy sets. This method is easy to be implemented in analog hardware. The effect of quantization levels on defuzzified fuzzy inference results is investigated. A few quantization levels are sufficient for fuzzy control. The hardware implementation of this calculation method and the defuzzification by gravity center method by PWM are also presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1050-1057
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• 2004

The purpose of study is development of a fuzzy controller which independent of a computer and its software for fuzzy control of servo system. This paper describes a method of approximate reasoning for fuzzy control of servo system, based on decomposition of $\alpha$-level fuzzy sets, It is propose that fuzzy logic algorithm is a body from fuzzy inference to defuzzificaion in cases where the output variable u directly is generated PWM. The effectiveness of quantified $\alpha$-levels on input/output characteristics of fuzzy controller and output response of DC servo system is investigated. It is concluded that $\alpha$-cut 4 levels give a sufficient result for fuzzy control performance of DC servo system. The experimental results shows that the proposed hardware method is effective for practical applications of DC servo system.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.8
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• pp.1246-1253
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• 2009

This paper presents derived a calculating form of fuzzy inference, based on decomposition of $\alpha$-level sets. Based on the calculating form it is propose that fuzzy logic circuits of PI+PD controller are a body from fuzzy inference to defuzzificaion in cases where the command variable u directly is generated PWM. The effect of quantization on $\alpha$-levels is investigated. with input/out characteristics of fuzzy controller by simulation. It is concluded that 4 quantization levels are sufficient result for fuzzy control performance of DC servo system. Simulation and experimental results demonstrated that the hardware implementation of the proposed controller can successfully provide good performance on the position control of DC servo system.

• Proceedings of the KIPE Conference
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• 2008.06a
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• pp.127-129
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• 2008

This paper describes a method of approximate reasoning for fuzzy control of servo system, based on decomposition of -level fuzzy sets. It is propose that logic circuits for fuzzy PI+PD are a body from fuzzy inference to defuzzificaion in cases where the output variable u directly is generated PWM. The effectiveness for robust and faster response of the fuzzy control scheme is verified for a variable parameter by comparison with a PID control and fuzzy control. A position control of DC servo system with a fuzzy logic controller successfully demonstrated.