• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.483-485
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• 1998

Neural Network has advantages of learning and normalizing capabilities. Fuzzy controller is based on a fuzzy logic that is so effective to represent uncertain phenomena of real world and make its approximation. In this paper, Fuzzy Neural Network controller which equipped with adaptive control algorithm is described. Proposed Fuzzy Neural Network Controller applied to a ball on beam system which have nonlinear characteristics shows a good performance.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.630-632
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• 1997

A fuzzy controller is based on o fuzzy logic that is so effective to represent uncertain phenomena of real world end mote its approximation. In this paper, A fuzzy controller which equipped with adaptive control algorithm is described. Proposed fuzzy controller applied to a boll on boon system shows a good performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.236-241
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• 2007

This paper presents an adaptive controller using chaotic dynamic neural networks(CDNN) for nonlinear dynamic system. A new dynamic backpropagation learning method of the proposed chaotic dynamic neural networks is developed for efficient learning, and this learning method includes the convergence for improving the stability of chaotic neural networks. The proposed CDNN is applied to the system identification of chaotic system and the adaptive controller. The simulation results show good performances in the identification of Lorenz equation and the adaptive control of nonlinear system, since the CDNN has the fast learning characteristics and the robust adaptability to nonlinear dynamic system.

• Journal of Power Electronics
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• v.6 no.3
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• pp.226-234
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• 2006

Photovoltaic (PV) generators have nonlinear V-I characteristics and maximum power points which vary with illumination level and temperature. Using a maximum power point tracker (MPPT) with an intermediate converter can increase the system efficiency by matching the PV systems to the load. This paper presents a maximum power point tracker based on fuzzy logic and a control scheme for a single-phase inverter connected to the utility grid. The fuzzy logic controller (FLC) provides an adaptive nature for system performance. Also the FLC provides excellent features such as fast response, good performance and the ability to change the fuzzy parameters to improve the control system. A single-phase AC-DC inverter is used to connect the PV system to the grid utility and local loads. While a control scheme is implemented to inject the PV output power to the utility grid at unity power factor and reduced harmonic level. The simulation results have shown the effectiveness of the proposed scheme.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3647-3653
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• 2012

In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal case. For better convergence speed in adaptive algorithms, fuzzy LMS algorithms where convergence coefficient computed by a fuzzy PI type controller was proposed.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.5
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• pp.42-49
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• 2001

In This paper, we present a collaborative method for material delivery using a distributed vehicle agents system. Generally used AGV(Autonomous Guided Vehicle) systems in FA(Factory Automation) require extraordinary facilities like guidepaths and landmarks and have numerous limitations for application in different environments. Moreover in the case of controlling multi vehicles, the necessity for developing corporation abilities like loading and unloading materials between vehicles including different types is increasing nowadays for automation of material flow. Thus to compensate and improve the functions of AGV, it is important to endow vehicles with the intelligence to recognize environments and goods and to determine the goal point to approach. In this study we propose an interaction method between hetero-type vehicles and adaptive fuzzy logic controllers for sensor-based path planning methods and material identifying methods which recognizes color. For the purpose of carrying materials to the goal, simple color sensor is used instead of intricate vision system to search for material and recognize its color in order to determine the goal point to transfer it to. The technique for the proposed method will be demonstrated by experiment.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.4
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• pp.349-358
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• 2013

In this paper, the sensorless MPPT algorithm is proposed where the performance of varied duty ratio change has been improved using multi-layer neuro-fuzzy that aligns with neuro-fuzzy based optimized membership function. Since the change of duty ratio of sensorless MPPT is varied by using the neuro-fuzzy, the MPPT response speed is faster than the convectional method and is able to reduce the steady-state ripple. The neuro fuzzy controller has the response characteristics which is superior to the existing fuzzy controller, because of the usage of the optimal width of the fuzzy membership function. The effectiveness of the proposed method has been verified by simulations and experimental results.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1587-1599
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• 2017

This paper proposes a real-time implementation of an optimal operation of a double stage grid connected wind power system incorporating an active power filter (APF). The system is used to supply the nonlinear loads with harmonics and reactive power compensation. On the generator side, a new adaptive neuro fuzzy inference system (ANFIS) based maximum power point tracking (MPPT) control is proposed to track the maximum wind power point regardless of wind speed fluctuations. Whereas on the grid side, a modified predictive current control (PCC) algorithm is used to control the APF, and allow to ensure both compensating harmonic currents and injecting the generated power into the grid. Also a type 2 fuzzy logic controller is used to control the DC-link capacitor in order to improve the dynamic response of the APF, and to ensure a well-smoothed DC-Link capacitor voltage. The gained benefits from these proposed control algorithms are the main contribution in this work. The proposed control scheme is implemented on a small-scale wind energy conversion system (WECS) controlled by a dSPACE 1104 card. Experimental results show that the proposed T2FLC maintains the DC-Link capacitor voltage within the limit for injecting the power into the grid. In addition, the PCC of the APF guarantees a flexible settlement of real power exchanges from the WECS to the grid with a high power factor operation.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.3
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• pp.111-119
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• 2002

This paper proposes a speed control system based on a fuzzy logic approach, integrated with a simple and effective adaptive algorithms. And this paper attempts to provide a thorough comparative insight into the behavior of induction motor drive with PI, direct and improved fuzzy speed controller. A indirect vector controlled induction motor is simulated under varying operating condition. The validity of the comparative results is confirmed by simulation results for induction motor drive system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.307-310
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• 1997

In case of environment requiring safety such as human body and requiring flexible shape, a conventional mechanical actuator system does not satisfy requirement. Therefore, in order to solve this problem, a research of various smart material such as EAP (Electro Active Polymer), EAC (Electro Active Ceramic) and SMA (Shape Memory Alloy) is in progress. Recently, the highest preferring material among various smart material is EP (Electrostictive Polymer), because it has very fast response time, poerful force and large displacement. The previous researches have been studied properties of polymer and simple control, but present researches are studied a polymer actuator. An EP (Electostrictive Polymer) actuator has properties which change variably as shape and environmental condition. Therefore, in order to coincide with a user's purpose, it is important not only to decide a shape of actuator and mechanical design but also to investigate a efficient controller. In this paper, we constructed the control logic with an adaptive fuvy algorithm which depends on the physical properties of EP that has a dielectric constant depending on time.