• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.58 no.3
• /
• pp.249-256
• /
• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive learning mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control (FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, FLC and ANN controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2009.05a
• /
• pp.416-419
• /
• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.627-630
• /
• 2004

The PID type controller has been widely used in industrial application due to its simply control structure, ease of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. This paper presents a hybrid fuzzy logic proportional plus conventional integral derivative controller (fuzzy P+ID). In comparison with a conventional PID controller, only one additional parameter has to be adjusted to tune the fuzzy P+ID controller. In this case, the stability of a system remains unchanged after the PID controller is replaced by the fuzzy P+ID controller without modifying the original controller parameters. Finally, the proposed hybrid fuzzy P+ID controller is applied to BLDC motor drive. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1997.10a
• /
• pp.70-75
• /
• 1997

This paper proposes a new approach to the design of fuzzy-neuro control for track vehicle system using fuzzy logic based on neural network. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

• Proceedings of the KIEE Conference
• /
• 1991.07a
• /
• pp.548-551
• /
• 1991

The Sliding Mode Control of Variable Structure System is applied to robot manipulators or servo system for its merits of robustness to variable system parameters and disturbances. But Switching frequency of control input is excessively high during sliding mode operation. In this paper, a new control algorithm usings fuzzy logic is proposed to solve this problem. With the proposed algorithm, a dc motor speed control system has been simulated and the result shows expected performances.

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

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1997.12a
• /
• pp.155-166
• /
• 1997

• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2307-2309
• /
• 2004

This paper presents a modeling and simulation of a fuzzy controller for maximum power extraction of a grid-connected wind energy conversion system with a link of a rectifier and an inverter. It discusses the maximum power control algorithm for a wind turbine and proposes, in a graphical form, the relationships of wind turbine output, rotor speed, power coefficient, tip-speed ratio with wind speed when the wind turbine is operated under the maximum power control. The control objective is to always extract maximum power from wind and transfer the power to the utility by controlling both the pitch angle of the wind turbine blades and the inverter firing angle. Pitch control method is mechanically complicated, but the control performance is better than that of the stall regulation method. The simulation results performed on MATLAB will show the variation of generator's rotor angle and rotor speed, pitch angle, and generator output.

• Journal of Biosystems Engineering
• /
• v.21 no.2
• /
• pp.175-181
• /
• 1996

Autonomous speedsprayer operation was conducted using the developed FLC(Fuzzy Logic Controller). Orchard image and signals of ultrasonic sensors were processed in real time. The speedsprayer was modified to be steered by two hydraulic cylinders. The FLC has two inputs, direction of running and distance from obstacles. The operation time of hydraulic cylinders were inferred as output of the FLC. Field test results showed that the speedsprayer could be autonomously operated by the FLC along with the image processing and the ultrasonic sensors. The ultrasonic sensors didn't contribute to the improvement of guidance performance, but the speedsprayer could avoid trees or obstacles in emergent situations with them.

• Journal of the Korean Society of Industry Convergence
• /
• v.4 no.2
• /
• pp.127-132
• /
• 2001

In turning, the chip may be produced in the form of continuous chip or discontinuous chip. The continuous chips are dangerous to the operator and difficult to be handled at high speed machining. The signal of AE(Acoustic Emission) is found out to be related to cutting conditions, tool materials, test conditions and tool geometry in turning. In this study, the relationship between AE signal and chip form was experimentally investigated. The experimental results show that the types of chip form are possible to be classified from the AE signal using fuzzy logic.