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

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.12a
• /
• pp.135-138
• /
• 2002

본 논문에서는 비최소위상 시스템으로 표현되는 화력발전소 드럼의 수위제어를 위한 퍼지 제어기를 제안한다. 제안된 방법은 T. Takagi와 M. Sugeno의 퍼지모델을 기반으로 수행된다. 그리고 기존의 PID 및 LQ 제어기법을 적용한 방식과 비교하여 제안된 방법의 개선된 특성을 시뮬레이션 결과로부터 검증하였다.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.724-727
• /
• 1997

This paper describes a control method of tank level using Fuzzy Inference Technique. In General, to control tank level without a dangerous overflow and with a high accuracy is difficult because of high order time delay and nonlinearity. None the less, the hardware controller using 80586 Microprocessor with DT-2801 board in this paper was successfully implemented, through a series of simulations and experiments, the superiority of the proposed fuzzy controller ta a conventional PID one was investigated.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.830-832
• /
• 1995

A position Control algorithm of the flexible manipulator is studied. The proposed algorithm is based on a Fuzzy Logic Control(FLC) method using the human's experiences. FLC does not need a dynamic modeling of a flexible manipulator. A Fuzzy logic controller is designed that the end-point of the flexible manipulator tracks the desired trajectory. The control input to the process is determined by the error and variation of error. Simulation result shows a robustness of FLC compared with the PID control algorithm.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.316-318
• /
• 1993

In order to estimation the optimum PID parameter of the turbine speed controller, the response cure of the object plant was compared with the reference pattern and then the magnitude peak value error and peak time error was calculated. With the calculated errors as input into the Fuzzy inference Method was introduced to propose the tuning method for each parameter. And the computer simulation was performed with the above Fuzzy inference method in which the Chunju hydro power plant turbine governor system was used as a model. This Study also aims to develop the exclusive tuner for govenor using industrial computer.

• Proceedings of the KIEE Conference
• /
• 2001.11c
• /
• pp.223-226
• /
• 2001

A SMA actuator fabricated in this paper generates the large force and it's structure is very simple. The SMA actuator was fabricated by small size with diameter of 4mm and length of 38mm and also it's actuations toward all the directions can be acquired because of three SMA springs which was fabricated with diameter of 1.2mm and 30 turns. We showed into applicability to smart catheter by analyzing accurately the dynamic characteristics such as heading angle, bending angle, force, displacement. For verifying control capacity of the fuzzy controller, we compared Fuzzy controller with PID controller by simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.153-156
• /
• 2000

This paper presents an PID type fuzzy based method for nohnear engine idle controller The output is a duty cycle(DC) for driving a idle speed cont개l valve(1SCV). For precise control of SI engine, the CPS sensor and coolant temperature are used. Visual C* language is used to make simulation panel for the fast and precise idle speed control. The dSPACE board and supported Control desk program is used in experiment ta the same purpose as simulation. The experimental results have a good agreement with simulation ones.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.5
• /
• pp.525-532
• /
• 2004

Telemanipulator is distingushed from industrial robot by iterating same specified work. Manipulator operator is included in control loop for controlling the telemanipulator because he decide directly during the work and order controllabily. We implement fuzzy controller for reducing the modelling error of telemanipulator which depend on the PID controller. But position-force control method of bidirectional control impose unsafety of vibiration and Analytic Hierchy method can stabilize for reducing nonlinear modelling error by expert operator because of transformation empirical control rule to linear model.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.766-771
• /
• 1993

A mathematical model is developed to represent the batch reactor for free radical polymerization of PMMA The model is validated by comparing the simulation result with the experimental data. A computational scheme is proposed to determine the trajectory of the reactor temperature that will produce polymer product having the desired molecular weight distribution. For this instantaneous number average chain length and polydispersity are introduced to calculate the reactor temperature. The former is assumed to be a second order polynomial of the sum of the living and dead polymer concentrations. Various reactor temperature, trajectories are observed depending on the reactor conditions and prescribed molecular weight distributions. Fuzzy and PID control algorithms are applied to trace the reactor temperature trajectory. While the PID control gives rise to an overshoot when the trajectory changes its direction, the fuzzy controller yields a more satisfactory performance because it secures information on the trajectory pattern.

• Proceedings of the KIEE Conference
• /
• 1995.07b
• /
• pp.999-1001
• /
• 1995

In this study, the algorithm of optimal parameter inference is proposed. At this inferring method, we tried to acquire the follow-up to reference pattern through comparing the plant output pattern with random reference pattern. As an inference method, the fuzzy theory was applied and the proposed algorithm was proved by computer simulation.