• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.206-211
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• 2011

In this paper, a control algorithm for the improvement of yaw and velocity stability of electrical vehicle with two or four in-wheel motors is proposed. The vehicle is modeled with independently operative in-wheel motor wheels. Different frictions on the wheels are regarded as disturbances, which causes driving instability. In this situation the proposed algorithm enables stabilizing the yaw motion and velocity of vehicle simultaneously. The proposed PID controller is composed with two techniques, which enhance the disturbance reject and point tracking performances. One is nonlinear gain function and the other one is improved integral controller operating as time based weight function. Simulation is conducted to reveal its efficient performance.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.702-704
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• 1997

In this paper, we applied self-tuning controller with I-PD type to process with time delay's. Process parameters are estimated by the recursive least squares algorithm, and optimal gains are obtained. This paper shows self-tuning controller with I-PD type performs better than that of general PID type for the nonlinear system with sudden change of set-points.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2345-2348
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• 2003

This paper deals with a problem of automatic landing guidance and control system design. The auto-landing control system for the longitudinal motion is designed in the classical PID controller. The controller gains are properly adapted to variation of the performance using fuzzy logic as a gain scheduler for the PID gains. This control logic is applied to the problem of the automatic landing control system design. From the numerical simulation using the 6DOF nonlinear model of the associated airplane, it is shown that the auto-landing maneuver is successfully achieved from the start of the flight conditions: 1500 ft altitude, 250 ft/sec airspeed and zero flight path angle.

• Journal of Power Electronics
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• v.9 no.5
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• pp.800-808
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• 2009

This paper presents a practical method of pressure control for a hydraulic oil-pump system using an SR (Switched Reluctance) drive. For a 6Mpa grade hydraulic oil-pump, a 2.6kW SR drive is developed. In order to get high performance pressure dynamics in actual applications, a data based PID control scheme is proposed. The look-up table from a pre-measured data base produces an approximate current reference based on motor speed and oil-pressure. A PID controller can compensate for the pressure error. With the combination of the two references, the proposed control scheme can achieve fast dynamics and stable operation. Furthermore, a suitable current controller considering the nonlinear characteristics of an SRM (Switched Reluctance Motor) and practical test methods for data measuring are presented. The proposed control scheme is verified by experimental tests.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2333-2335
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• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process(ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of a wastewater, the change of an influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains can be adjusted by the expert in the ASP. The ASP model based on Matlab$^{(R)}$5.3/Simulink$^{(R)}$3.0 is developed in this paper. Various control methods are applied to the ASP model and the control results are disscussed. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.289-292
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• 2005

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But it is difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose an adaptive PID controller based on a gradient descent learning. This algorithm has a simple structure like conventional PID controller and robustness to system parameters variation. To verify performances of the proposed adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.5
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• pp.241-248
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• 2000

Until now, all of the port goods are transported manually by container transporter in the port. Recently there are a lot of studies about unmanned vehicle driven automatically. In terms of the vehicle automation, the control of steering and velocity on vehicle systems is very important part in container transporter. In common sense, vehicle systems have lots of nonlinear parameters so we have many difficulties in designing the optimal controller of them. In this paper, we present a design of the TDOF PID controller using a hybrid schematic algorithm to control the steering system optimally. We used the single-track model to pre-test the designed controller before appling to AGV. We also used the ES(evolutionary strategy) and SA(simulated annealing) algorithms to construct the hybrid tuning algorithm for parameters of controller. Finally, we had the computer simulation to verify that our designed controller has better performance than the other one.

• Journal of Power System Engineering
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• v.19 no.3
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• pp.48-54
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• 2015

This paper introduced a design method of soldering station that can control two types of soldering iron heater. At design time, to distinguish two types of soldering iron heater the voltage divider rule has been applied, and the distinguished resistor is inserted to handler of soldering iron to prevent misuse by users. And an algorithm to design a PID controllers is proposed. The proposed controllers parameter which can be easily realized, and are designed by using the input output data from systems, and have outstanding ability making the output response of nonlinear systems similar to the desired one. Temperature control experiments were performed to verify the ability of the suggested controller. As a result, suggested PID controller followed the desired ones, and one soldering station can control the various type of soldering irons in real time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.748-753
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• 1996

The contact roll is often used to regulate the winding tension as well as the entrained air in a wound roli by adjusting the contact force to the winding roll. But the contact force generated by other rolls, like assistant nip rolls, in a winding(or roll changing) process may act as disturbance to the control of the winding tension. In this paper, the mechanism of a roll change process is analyzed. And, the behavior of the contact and the assistant nip rolls are mathematically modeled. A nonlinear PID(NPID) controller is designed to control the winding tension and to reject the effect of disturbance generated by the assistant nip roll on the winding tension variation. Computer simulation study showed that the performance of the suggested NPID controller is improved compared with that of the PID controller in con trolling the winding tension and in rejecting the effect of the disturbance.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.209-214
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• 1998

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.