• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1327-1334
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• 1999

The stabilization control of ball-beam system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of classical methods such as the PID and the full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Therefore, in this paper, three improved design techniques of stabilization controller for a ball-beam system were proposed. These parameter tuning methods in the double PID controller(DPIDC), the FSFC and the a sliding mode controller(SMC) were dependent upon the Real Value Elitist Genetic Algorithm (RVEGA). Finally, by applying the DPIDC, the FSFC and the Real Variable Elitist Genetic Algorithm based Sliding Mode Control(RVEGA SMC) to the stabilizations of a ball-beam system, the performances of the RVEGA SMC technique were showed to be superior to those of two other type controllers.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.134-141
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• 2003

PID controllers with constant gains have been widely used in various control systems due to its powerful performance and easy implementation. But it is difficult to have uniformly good control performance in all operating conditions. In this paper, we propose a nonlinear variable PR controller with immune feedback mechanism. An immune feedback mechanism is based on the functioning of biological T-cells, they include both an active term, which controls response speed. and an inhibitive term, which controls stabilization effect. Therefore, the proposed nonlinear PID controller is based on immune responses of biological. immune feedback mechanism which is the cell mediated immunity and In order to choose the optimal nonlinear PID controller games, we also propose the tuning algorithm of nonlinear function parameter in immune feedback mechanism. To verify performance of the proposed algorithm, the speed control of nonlinear DC motor are performed. Front the simulation results, we have found that the proposed algorithm is more superior to the conventional constant fain PID controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.228-231
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• 2000

A hybrid fuzzy controller by means of the genetic algorithms is presented. The control input for the system in the HFC is a convex combination of the FLC's output in transient state and PlD's output in steady state by a fuzzy variable. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller. A auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller using genetic algorithms. The algorithms estimates automatical Iy the optimal values of scaling factors, PID parameters and membership function parameters of fuzzy control rules. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA three kinds of estimation modes are effectively utilized. The HFCs are applied to the second process with time-delay. Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed in ITAE(Integral of the Time multiplied by the Absolute value of Error ) and other ways.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2655-2657
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• 2000

this paper suggests a genetic algorithms combining simulated annealing for PID factor tunning. This paper made Off-Line control parameter tuning of the DC servo motor for the speed, In this paper new method to design PID controller through proposed genetic algorithm. Two experiments compared both the PID controller using genetic algorithms and PID controller using proposed genetic algorithm for a DC-servo motor. The result of two experiments was safty higher PID controller using proposed genetic algorithm than PID controller using genetic algorithm.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.462-465
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• 2001

The wound induction motor can provide high starting torque and reduced starting current simultaneously by inserting large scale resistor. And this technique is one of the well known methods among the induction motor starting methods and generally used for heavy load starting such as Crain and Cement factories. The conventional PI controller has been widely used in industrial application due to the simple control algorithm and in general, PI controller is used for control of current, torque, position, and speed for the wound induction motor drive system. However, the system may result in poor performance since sensors have to be used, which in turn is limited by the environmental condition. Recently, to overcome these problems, many sensorless vector control methods for the wound induction motor have been studied. This paper presents MRAS method with on-line stator resistance tuning for sensorless vector control of the wound induction motor drive. In conventional MRAS method, in low frequency, stator resistance variation can result in poor performance. Therefore, to overcome several shortages of the conventional MRAS caused by parameter variation and enhance robustness of the sensor less vector control, this paper investigates a MRAS method with on-line stator resistance tuning for sensorless vector control of the wound induction motor. The validity and effectiveness of the proposed method is verified through digital simulation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.24-31
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• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.12
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• pp.589-594
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• 2000

The fuzzy controllers have been applied to the power system stabilizer due to its excellent properties on the nonlinear systems. But the design process of fuzzy controller requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This process is time consuming task. This paper presents an parameters tuning method of the fuzzy power system stabilizer using the genetic algorithm and simulated annealing(SA). The proposed method searches the local minimum point using the simulated annealing algorithm. The proposed method is applied to the one-machine infinite-bus of a power system. Through the comparative simulation with conventional stabilizer and fuzzy stabilizer tuned by genetic algorithm under various operating conditions and system parameters, the robustness of fuzzy stabilizer tuned by proposed method with respect to the nonlinear power system is verified.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.90-94
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• 2004

Among various modern control theories, PID control has been well used for several decades. PID algorithms needs son tuning methods are used for selecting PID parameters. But in some cases various kinds of performance indices are used instead of well-known tuning rules, and so variable type of performance index must be tested so that controllers, output characteristics and disturbance rejection property meets some specifications. In this paper, linear conbinational type of performance using error signal, time, control input and robustness is used to the PID control of air conditioning system. By the 2 DOF PID parmeters minimizing perfromacne index, controllers, output characteristics and robustness properties are analyzed. Simulations are done with MATLAB m file and mdl files.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.364-371
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• 2007

In this paper, we describe the synthesis of robust and non-fragile $H^{\infty}$ state feedback controllers for linear systems with affine parameter uncertainties, as well as a static state feedback controller with poly topic uncertainty. The sufficient condition of controller existence, the design method of robust and non-fragile $H^{\infty}$ static state feedback controller with fuzzy compensator, and the region of controllers that satisfies non-fragility are presented. We show that the resulting controller guarantees the asymptotic stability and disturbance attenuation of the closed loop system in spite of controller gain variations within a resulted polytopic region.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1380-1384
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• 2015

The DC motor has the strong characteristics in the speed response, the system parameter variations and the external influence and is used as the speed controller with its good starting torque in the distributing industry. However development of the Microprocessor which is for high speed switching program can make better control system. This paper introduce to design of the high-effective DC motor controller that is using Software Bang-Bang Program of Fuzzy algorithm and to verify a PI controller and a Fuzzy controller.