• Journal of Advanced Marine Engineering and Technology
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• 제30권7호
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• pp.791-799
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• 2006

The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.502-504
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• 1998

This paper proposes the method that estimate optimally the parameters of Fuzzy-PID controller using genetic Algorithm. The controller is designed with the proposed method, and then is applied to 3-phase induction motor. Simulation results show that proposed method is more excellent then FPID and PID.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1092-1095
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• 1996

In this paper The tuning of PID controller for multi input-output is studied by using fuzzy inference. State of coupling is estimated by fuzzy inference, its results is used for tuning of PID controller to get optimum P,I,D parameter with regard to state of coupling. This method is simulated to Turbo-generating system with $2{\times}2$ multi input-output and made with electronic circuit, its response is very satisfactory.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.67.1-67
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• 2001

This paper presents a neural network based self-tuning fuzzy PI-PD control scheme for robust speed control of induction motor. 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 PI-PD controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small ...

• International Journal of Automotive Technology
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• 제4권4호
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• pp.181-191
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• 2003

Since the nonlinearity and uncertainties which inherently exist in vehicle system need to be considered in active suspension control law design, this paper proposes a new control strategy for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a genetic algorithm (GA) based self-tuning PID controller and a fuzzy logic controller in two loops. In the control scheme, the PID controller is used to minimize vehicle body vertical acceleration, the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors. In order to improve the adaptability to the changes of plant parameters, based on the defined objectives, a genetic algorithm is introduced to tune the parameters of PID controller, the scaling factors, the gain values and the membership functions of fuzzy logic controller on-line. Taking a four degree-of-freedom nonlinear vehicle model as example, the proposed control scheme is applied and the simulations are carried out in different road disturbance input conditions. Simulation results show that the present control scheme is very effective in reducing peak values of vehicle body accelerations, especially within the most sensitive frequency range of human response, and in attenuating the excessive dynamic tire load to enhance road holding performance. The stability and adaptability are also showed even when the system is subject to severe road conditions, such as a pothole, an obstacle or a step input. Compared with conventional passive suspensions and the active vehicle suspension systems by using, e.g., linear fuzzy logic control, the combined PID and fuzzy control without parameters self-tuning, the new proposed control system with GA-based self-learning ability can improve vehicle ride comfort performance significantly and offer better system robustness.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권8호
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• pp.473-480
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• 2000

A fuzzy PID controller is proposed for the posture control of a two DOF robot vehicle inspecting the defects of the inner wall of sewage pipes. The main difficulty in controlling these kinds of vehicles lies in that the center of two mobile shafts does not coincide with the weight center of the vehicle due to its long and wide shape. In this case the previous controller, based on the assumption that the gap between these centers are small, can not guarantee satisfactory transient response characteristics. In this paper, this gap is included in the mathematical modelling of the robot kinematics, and in order to compensate the unsatisfactory transient response characteristics, the fuzzy PID controller is proposed. This controller tunes the PID control gains with respect to the current state of the errors between the reference and the current postures. A series of simulations has been performed to investigate the tracking performance of the proposed controller for the lane changing path and the robustness to the external disturbance. The simulation results show that the proposed controller has a satisfactory tracking performance in the transient state as compared with that of the backstepping control given in reference.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2005년도 전기학술대회논문집
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• pp.274-280
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• 2005

The system parameters of gas turbine engine tend to change remarkably in real operating condition. It means that operators have to consider environment and suitably control fuel flow. The conventional PID controller, however, can not guarantee good control performance in the aspect of system parameter change. This paper, therefore, proposes a scheme for integrating PID control and fuzzy technique to obtain the good performance of gas turbine engine speed control on the whole operating range. The effectiveness of the proposed fuzzy PID controller is verified through computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.228-228
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• 2000

To deal with non-linearities and time-varying characteristics of hydraulic systems, in this paper, the neuro-fuzzy controller has been introduced. This controller does not require an accurate mathematical model for the nonlinear factor. In order to solve general fuzzy inference problems, the input membership function and fuzzy reasoning rules are used for determining the controller Parameters. These parameters are determined by using the learning algorithm. The control performance of the neuro-fuzzy controller is obtained through a series of experiments for the various types of input while applying disturbances to the cylinder. .and performance of this controller was compared with that of PID, PD controller. As a experimental result, it can be proven that the position tracking performance of the neuro-fuzzy is better than that of PID and PD controller.

• 한국정밀공학회지
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• 제15권9호
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• pp.56-67
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• 1998

This paper introduces a friction compensation fuzzy logic controller, which utilizes a rule-based approach. The paper explains the algorithm of the proposed controller and compares it with a conventional PID controller in simulations and experiments. For the experiments, the two control algorithms were implemented on a 3-axis milling machine in contour milling. These simulation and experimental analyses show that the proposed fuzzy logic controller has superior performance over conventional PID controllers In terms of part contour accuracy.

• 한국지능시스템학회논문지
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• 제24권1호
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• pp.102-109
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• 2014

TSK 퍼지 시스템의 뛰어난 성능을 일반 산업 현장에서 가장 많이 사용되고 있는 PID 제어기에 접목시켜, 비선형 시스템의 제어가 가능하고 강인성이 뛰어난 퍼지 PID 제어기의 설계를 제안한다. TSK 퍼지 제어기는 TSK 퍼지 모델로부터 극 배치법을 이용하여 설계되며, 비선형 시스템의 제어에서 시스템의 응답이 원하는 응답과 같아지도록 하는 뛰어난 능력이 있으나 구조가 복잡하여 산업 현장에서 사용되기에는 어려움이 있다. 본 연구에서는 구현하기 간편한 PID 제어기의 형태를 하면서, TSK 퍼지 제어기의 도움을 받아 설계되는 퍼지 PID 제어기를 제안한다. 즉, 먼저 비선형 시스템의 TSK 퍼지 제어기를 설계하고 그 TSK 퍼지 제어기의 제어 시뮬레이션으로부터 얻은 데이터를 이용하여 제안하는 퍼지 PID 제어기를 설계한다. 제안하는 제어기를 연속시간 비선형 시스템과 이산시간 비선형 시스템의 예제에 적용시켜 제어 시뮬레이션을 하였다. 그 결과 기존의 선형 PID 제어기로는 제어가 원만하지 않았으나 제안하는 제어기로는 원하는 응답 형태와 거의 같은 응답을 보이는 제어가 가능함을 알 수 있었다.