• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.1
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• pp.36-43
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• 2003

This paper presents an optimal tuning method for Fuzzy Logic Controller (FLC) of current controller for HVDC using Genetic Algorithm(GA). GA is probabilistic search method based on genetics and evolution theory. The scaling factors of FLC are tuned by using real-time GA. The proposed tuning method is applied to the scaled-down HVDC simulator at Korea Electrotechnology Research Institute(KERI). Experimental result shows that disturbances are well-damped and the dynamic performances of FLC have the better responses than those of PI controller for small and large disturbances such as ULTC tap change, reference DC current change and DC ground fault.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.399-405
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• 2007

This paper deals with the controller for a stable walking of a humanoid robot using genetic algorithm. A humanoid robot has instability during walking because it isn't fixed on the ground, and its nonlinearities of the joints increase its instability. If controller isn't robust, the robot may fall down at the ground during walking because of its nonlinearities. To solve this problem, robust controller is required to reduce the effect of nonlinearities and to gain the good tracking performance. In this paper, motion controller that is based on fuzzy-sliding mode controller is proposed. This controller can remove the effect of the saturation by limitation of the input voltage. It also includes compensator for reducing the effect of the nonlinearity by backlash and PI controller improving the tracking performance. In here, genetic algorithm is used for searching the optimal gains of the controller. From the given controller, a humanoid robot can moved more preciously. All the processes are investigated through simulations and are verified experimentally in a real joint system for a humanoid robot.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.249-256
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• 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
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• 2008.05a
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• pp.440-444
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• 2008

The 7-phase BLDC motor is possible for higher efficiency per the unit area, high power and high speed due to the increasing number of phase. Also, it can be looking forward to reduce the current ripple at a point of commutation by the increasing number of phase. Thus, a study for applications of servo system, medical and military instruments is progressing about the BLDC motor is manufactured with multi-phase, currently. This paper is used the fuzzy logic control method for speed control of 7-phase BLDC motor and this is compared with the conventional PI controller using by simulation and experimental results for verification validity of the fuzzy logic controller in this system. The 7-phase BLDC motor and controller are modeled by PSIM6.0 software of PowerSim co. in simulation and we are experimented by the test board that is composed with TMS320VC33-150 DSP controller of Texas Instruments co. and FLEX EPF6016TC144-3 of ALTERA co.

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

• Proceedings of the KIPE Conference
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• 2010.11a
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• pp.276-277
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• 2010

This paper describes the control of a utility-connected doublefed induction machine (DFIM) for wind power generation systems (WPGS). Real and reactive powers (PQ) at the stator side of DFIM are strictly controlled to supply the power to the grid without any problems. In this paper the control is realized using Fuzzy PI controller based on the stator-flux orientation control.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.650-652
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance. FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and increase efficiency, a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy Pi and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and them. The resultant rule base is Macvicar-Whelan type. The frequency response information is used in tuning of membership functions. Also a tuning strategy for the scaling factors is Proposed based on the relationship between PID gain and them. Simulation results show better performance and the effectiveness of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.83-87
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• 2005

This paper deals with the design and evaluation of the robust controller for a synchronous generator excitation system to improve the steady state and transient stability. The nonlinear characteristics of the system is treated as model uncertainties, and then the robust control techniques are introduced into the power system stability design to take into account these uncertainties at the controller design stage. The performance of the designed controller is examined by extensive non-linear time domain simulation. It is shown that the performance of the robust controller is superior to that of the conventional PI controller. This paper also proposes an improved digital exciter control system for a synchronized generator using a digitally designed controller with database. Results show that the proposed control system manifests excellent control performance compared to existing control systems. It has also been confirmed that it is easy for the proposed control system to implement digital control.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.109-114
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• 2002

Various inverted pendulum systems have been frequently used as a model for the performance test of the proposed control system. We first identify a rotary-type inverted pendulum system by the Euler-Lagrange method and then design a FLC (Fuzzy Logic Controller) fur the plant. FLC`s are one of useful control schemes fur plants having difficulties in deriving mathematical models or having performance limitations with conventional linear control schemes. Many FLC`s imitate the concept of conventional PD (Proportional-Derivative) or PI (Proportional-Integral) controller. That is, the error e and the change-of-error are used as antecedent variables and the control input u the change of control input Au is used as its consequent variable for FLC`s. In this paper we design a simple-structured FLC for the rotary inverted pendulum system. We also perform some computer simulations to examine the tracking performance of the closed-loop system.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.243-244
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• 2008

In this paper proposed the solar tracking system to use a fuzzy based on PC in order to increase an output of the PV array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.