• Journal of Advanced Marine Engineering and Technology
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• v.31 no.3
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• pp.293-300
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• 2007

The aim of this paper is to design a speed controller of a DC motor by selection of a PID parameters using genetic algorithm. The model of a DC motor is considered as a typical non-oscillatory, second-order system, And this paper compares three kinds of tuning methods of parameter for PID controller. One is the controller design by the genetic algorithm. second is the controller design by the model matching method third is the controller design by Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the genetic algorithm is better than the Ziegler & Nickels' method. And also found that the results of the method by the genetic algorithm is nearly same as the model matching method which is analytical method. The proposed method could be applied to the higher order system which is not easy to use the model matching method.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.421-424
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• 2008

In torque transmission system, we must suppressed vibration for Accuracy characteristic response of motor, Therefore, vibration suppression factor is very important motor control. To suppress vibration, a various control method has been proposed. Specially, one method of vibration suppression used disturbance observer filter. This method is torsion torque passing disturbance observer filter. By the estimated torsion torque feedback, vibration can be suppressed. The CDM(coefficient diagram method) is used to design the filter and Proportional controller. But using coefficient diagram method, not adapted controller parameter in disturbance. For this solution, we used fuzzy controller for auto tuning controller parameter. We proved this approach is confirmed by simulation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.325-330
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• 2006

Integrating processes are frequently encountered in process industries. Generally they are most commonly associated with level control problems. In this paper, tuning formulae of PID controllers for set-point tracking and load disturbance rejection are presented on integrating processes with time delay. In particular, the controller parameters are determined such that performance criteria(IAE, ISE and ITSE) are minimized. Optimal PID parameter sets are obtained by means of a real-coded genetic algorithm(RCGA) and then tuning rules are addressed using obtained PID parameter sets and another RCGA. The performances of the proposed tuning rules are tested on two processes.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.759-760
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• 2006

In this paper proposed to Neural network PI self-tuning direct controller using Error back propagation algorithm. Proposed controller applies to speed controller and current controller. Also, this built up the interface environment to drive it simply and exactly in any kind of reference, environment fluent and parameter transaction of BLDC motor. Neural network PI self-tuning simulator using Visual C++ and Matlab Simulation is organized to construct this environment. Built-u-p interface has it's own purpose that even the user who don't have the accurate knowledge of neural network can embody operation characteristic rapidly and easily.

• Journal of Ocean Engineering and Technology
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• v.3 no.2
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• pp.551-551
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• 1989

In general, a remotely operated vehicle(ROV) operates at deep sea. The control system of ROV is composed of two local loops; the first loop placed on the surface vessel monitors and manipulates the attitude of the ROV using joystick, and the second part on the ROV automatically controls thrusters and acquires positional data. This paper presents a position control simulation of a ROV using an adaptive controller and discusses the control effects of two different conditions. The design of an adaptive control system is obtained by the application of a self-tuning controller with the minimization of an appropriate cost function. The parameters of the control system are estimated by a recursive least square method(RLS). In the simulation, a Runge-Kutta method is used for the numerical integration and the generated outputs are obtained by adding measurement errors. Additionally, this paper discusses the mathematical modelling of a ROV and make a survey of control systems.

• Journal of Ocean Engineering and Technology
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• v.3 no.2
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• pp.51-58
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• 1989

In general, a remotely operated vehicle(ROV) operates at deep sea. The control system of ROV is composed of two local loops; the first loop placed on the surface vessel monitors and manipulates the attitude of the ROV using joystick, and the second part on the ROV automatically controls thrusters and acquires positional data. This paper presents a position control simulation of a ROV using an adaptive controller and discusses the control effects of two different conditions. The design of an adaptive control system is obtained by the application of a self-tuning controller with the minimization of an appropriate cost function. The parameters of the control system are estimated by a recursive least square method(RLS). In the simulation, a Runge-Kutta method is used for the numerical integration and the generated outputs are obtained by adding measurement errors. Additionally, this paper discusses the mathematical modelling of a ROV and make a survey of control systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.3
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• pp.40-50
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• 1996

By using the neural networks(NN) as system identifier, the on-line self tuning method for fuzzy controller(FC) is proposed. In theis method, the learning of NN is carried out during control operation of FC and the cinsequent parameters of FC is tuned on-line automatically by means of system output errors backpropagated through NN. The Sugeno fuzzy model with constants as consequent parameters is selected for simplifying computation. In procedures of parameter tuning, the gradient descent method is used and the gradient vectors for adjusting the weight of NN are transferred as controller output errors. To evaluate the performance, the proposed method is applied to the inverted pendulum system.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.4
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• pp.195-202
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• 2002

The high performance position controller named 'Unified PID Position Controller'is presented in part 1 of this paper. In part 2, we provide smart gain adjustment methods including the freedom utilizations for rare sensitivity toward the system parameter variation and for increasing the stiffness of the system. Owing to the provided gain tuning strategy, the overall system characteristics can be stabilized without over-shoot phenomena when the system parameter is changed in the rate of from 0.5 to 2∼4. Moreover, for the actual feasibility to the industrial fields, a simple butt effective anti-windup strategy prohibiting the integral component of the PID position controller from saturation is presented too. All of the presented algorithms are verified through the experiment works with commercial linear motor.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.314-320
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• 2005

In this paper, a methodology for estimating the parameters of a discrete-time system and designing a digital PID controller based on the estimated model and a genetic algorithm is presented. To deal with optimization problems occurring regarding parameter estimation and controller design, a pseudo parallel genetic algorithm (PPGA) is used. The parameters of a discrete-time system are estimated using both the model technique and a PPGA. The digital PID controller is described by the pulse transfer function and its parameters are tuned based on both the model reference technique and another PPGA. A set of experimental works on two processes are carried out to illustrate the performance of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.5 s.236
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• pp.770-776
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• 2005

The gains fur NC controller parameter are fixed when the controller is combined with a machine. However, the characteristics of controller could be changed as it has being used by the machine or other environmental conditions. Those result in that the tool positioning accuracy is influenced. The loading torque in servo motor influences on the tool positioning accuracy and it is controlled by the parameter gains. It is required to analyze the torque variation with angular positioning accuracy of the servo motor. This study focus on a measuring method and device for verifying angular positioning accuracy of NC servo motor. We used a high resolution An converter for acquiring analogue signal of rotary encoder in servo motor. The positional accuracy for a nominal tool path, which is generated by the combination of axial movements (X,Y,Z), is analyzed with the servo motor torque. The current variation signal is acquired at the power line using a hall sensor and converted to the loading torque of servo motor. The method of measurement and analysis proposed in this study will be used for determining the gains of parameter in NC controller. This gain tuning is also necessary when the controller is set up at a machine.