• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.135-138
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• 1997

In this paper, Tuning method of the parameter P.I.D of the 2DOG-PID controller for having a required response to the disturbance and the setpoint is studied by the neural network. This algorithms is simulated in the level control of the steam generator and the flow control system, and resulting represents than the conventional PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.456-458
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• 1986

A method for on-line tuning of the PID-controller parameters for a discrete-time multivariable process system is presented. And it is based on a step change in the controller set point. The system is presumed to be a linear, open loop stable and known one. The controller parameters are determined by the performance criterion and Fletcher-Powell methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2493-2496
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• 2003

This paper presents an optimal tuning method of decentralized PID controller of two-input, two-output(TITO) second order system to be formulated as LQR.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1392-1395
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• 1996

Nonlinear PID controllers have increasingly used in current industrial practice because it is robust and is easy to operate. Little guideline and tuning method, however, has been recommended for the nonlinear PID controllers while a lot of result is available for the linear PID controllers. Application guideline and tuning formulae are presented for error square type nonlinear controllers, which are most popular currently, are presented.

• 대한전기학회논문지
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• 제39권5호
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• pp.478-484
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• 1990

An automatic tuning method of a PID controller which is used for single input single output processes is proposed. In the proposed tuning method, the frequency response data model is adopted along with the performance index which is an integral of time weighted square error between reference model and process frequency response data model for tuning. This method is easier to retune when either the process dynamics is changed or the reference model is changed. Finally, an example is provided to show the usefulness of the method.

• 대한전기학회논문지
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• 제40권8호
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• pp.774-781
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• 1991

This paper proposes an auto-tuning method of a discrete -PIC controllers which is based on the Ziegler and Nichols's PID Tuning Rule. This tunign rule is derived using the Pade's first order approximation and it prevents the performance degradation caused by the time-delay effect of zero order holder when the Ziegler-Nichols tuning rule is applied to a discrete PID controller. A simple and practical auto-tuning method is proposed through combining this discrete tuning rule with the relay control. The auto-tuning scheme is implemented on a microprocessor based system and is applied to a position control system to show the effectiveness of the discrete tuning rule.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 B
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• pp.1182-1184
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• 2001

This paper presents a neural network based self-tuning fuzzy PID control scheme for induction motor speed control. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PID controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink is performed to verify the effectiveness of the proposed scheme.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.50-54
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• 1997

In general, the design of fuzzy logic controller has difficulties in the acquisition of expert's knowledge. So, some methods that can optimize the parameters for fuzzy logic controller automatically without expert knowledge was provided. Recently, tuning method for fuzzy logic controller using genetic algorithm(GA) were proposed in many papers. However, those are tuning methods for a part or some part of fuzzy logic controller. In this paper, we proposes auto tuning method for the whole part of tuzzy logic controller, such as parameters of membership functions for antecedence and consequence parts, rule base, scaling factor and the number of rule. Finally, second order dead time plant is provided to show the advantages of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.238-242
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• 1991

This paper presents an approach to self-tuning PI control of dynamic plants, based on fuzzy logic application. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a fuzzy logic controller, one of the most difficult problem is the selection of linguistic control rules and parameters. To overcome this difficulty, self-tuning fuzzy PI controller (STFPIC) with a hierarchical structure in which the fuzzy PI controller is assigned as the lower level and the rule modification and parameter adjustment as the higher level. The rules and parameters are generated by the adjustment of membership function through performance index(PE). In this paper, the algorithm for of the controller performance is estimated by means of computer simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2470-2472
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• 2001

This paper describes the application of a fuzzy-tuning PID controller to a 3-DOF attitude control of a small model helicopter in hover for the compensation of coupling effects between each axis and system uncertainties due to the variation of engine RPM. A Low-level PID controller is designed by Ziegler-Nichols method and its gains are tuned by a high-level fuzzy system based on error states and its time derivatives. The experimental results show that the attitude control performance of fuzzy-tuning PID controller is improved comparing with that of a Ziegler-Nichols PID controller and fuzzy controller.