• Proceedings of the Korean Society of Marine Engineers Conference
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• 2000.05a
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• pp.6-10
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• 2000

In this paper a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a low-pass prefilter the inverse dynamic model of a system and the PI controller. The low-pass prefilter prevents high frequency effects from the inverse dynamic model. The model is characterized by a nonlinear friction model. The PI controller regulates the error between the set-point and the system output which is caused by modeling error disturbances and variations f parameters. The parameters of the model and the PI controller are optimized offlinely by genetic algorithm. The experimental results on a DC motor system illustrate the performance of the proposed controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.4
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• pp.33-42
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• 2010

The induction motor drive applied to field oriented control is widely used in industry applications. However, it is deceased performance and authenticity by saturation, temperature changing, disturbance and parameters changing because modeling of induction motor is nonlinear and complex. In order to control variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field oriented conditions. This paper proposes self tuning PI controller based on fuzzy-neural network(FNN)-PI controller that is implemented using fuzzy control, neural network, and adaptive fuzzy controller(AFC). Also, this paper proposes estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FNN-PI, AFC and ANN controller. Also, this paper proposes the anlysis results to verify the effectiveness of controller.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.457-460
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• 1996

An adaptive pH control is developed to manipulate the nonlinearities and time-varying properties of pH systems. In this research, we estimate two adjustable parameters by using the recursive least squares method and a nonlinear PI controller is used to control pH systems based on the estimated two parameters.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.2
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• pp.183-190
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• 2007

Controlling superheat of indoor units associated with a multi-type heat pump is one of difficult tasks to be addressed. This study suggests a dynamic model of an evaporator based on heat and mass balance. Thermodynamic properties are calculated by a commercial software, Refprop. The model is programmed in MFC Visual C++ for controller interface in real-time mode. The simulation results shows that PI control works for a narrow range of superheat. Beyond the range, the temperature behavior of the refrigerant is quite nonlinear mainly due to phase change. Thus, it is concluded that PI control of superheat has to be supplemented by nonlinear control ideas to avoid saturation and excessive superheat.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.994-996
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• 2000

Switched reluctance motor generally operates in the magnetically saturated region because the saturation gives several benefits to its performance. This paper investigates the modelling and fuzzy tuning PI control of a nonlinear switched reluctance motor. The modelling is performed through neural network technique. Fuzzy auto-tuning PI control is designed for a robust performance in load and speed variations. Simulation and experimental results indicate better performances compared with simple PI control.

• Proceedings of the KIEE Conference
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• 2005.10a
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• pp.155-157
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• 2005

This paper shows how to design a MPPT control of PV system using neural network PI self tuning. The conventional self-tuning methods have the voltage control problem of nonlinear PV system which can't adapt against any kinds of noise or operation circumstances. In this paper, supposed to solve these problem to PI parameters controller algorithm using ANN. In the proposed algorithm, the parameters of the controller were adjusted to reduce by on-line system the error of the output voltage of DC-DC chopper. In this process, EBPA NN was constituted to an output error value of a DC-DC chopper and conspired an input and output. The performance of the self-tuning controller is compared with that of the PI controller tuned by conventional method. The effectiveness of the proposed control method is verified thought the Matlab Simulink.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.146-156
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• 2003

Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,\dot{x},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1132_1133
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• 2009

In this paper, a observer-based PI controller will be developed for PEM fuel cell system. Nonlinear model of PEM fuel cell system is introduced to study the controller design problems. Sliding mode observer will be designed to estimate the cathode and anode pressures of PEMFC system. And a nonlinear state observer is also designed to estimate the other states such as supply manifold pressure, Oxygen pressure, Hydrogen pressure, return manifold pressure, etc. These estimated states are used to design the observer-based PI controller. The validity of the proposed controller will be verified by using computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.35-41
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• 2000

This paper describes the design of fuzzy digital PID controller using a simplified indirect inference method. First, the fuzzy digital PID controller is derived from the conventional continuous-time linear digital PID controller,. Then the fuzzification, control-rule base, and defuzzification using SIM in the design of the fuzzy controller are discussed in detail. The resulting controller is a discrete-time fuzzy version of the conventional PID controller, which has the same linear structure, but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIIM is applied the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated that the proposed method provides better control performance than the one proposed by D. Misir et al.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.3
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• pp.117-120
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• 2014

In general a main technology of control a sluice gate is accurate synchronous position control for the two cylinders when they are moving with the sluice gate together over 10[m]. Because the nonlinear friction and the unconstant supply flow. Cylinders' displacement will be different. In this case the sluice gate may be deformed and abraded, and even the sluice gate may unable to work. In order to design the controller for this system, we designed two kinds of Fuzzy PI controllers. Fuzzy PI position controller and Fuzzy PI synchronous controller have been designed. We show some simulation results for its availability.