• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.656-666
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• 1999

In this paper, we design the optimal PD control system which has the robust performance. This PD control system is designed by applying genetic algorithm (GA) to the determination of proportional gain KP and derivative gain KD that are given by PD servo controller, to make the output of plant follow the output of reference model optimally. These proportional and derivatibe gains are simultaneously optimized in the search domain guaranteeing the robust performance of system. And, this PD control system is compared with $\mu$ -synthesis control system for the robust performance. The PD control system designed by the proposed method has not only the robust performance but also the better command tracking performance than that of the $\mu$ -synthesis control system. The effectiveness of this control system is verified by computer simulation.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.795-797
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• 1998

This paper suggests a design method of the optimal PD control system having robust performance. This PD control system is designed by applying genetic algorithm(GA) with reference model to the optimal determination of proportional(P) gain and derivative(D) gain that are given by PD servo controller. These proportional and derivative gains are simultaneously optimized in the search domain guaranteeing the robust performance of closed-loop system. This PD control system is applied to the fuel-injection control system of diesel engine and compared with ${\mu}$ -synthesis control system for robust performance. The effectiveness of this PD control system is verified by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.483-483
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• 2000

The Fuzzy Preview Control (FPC) design methodology using I-PD Preview Control (IPC) and Optimal Preview Control (OPC)[6] are discussed in this paper. First we show a new fuzzy controller with single input single output, and build a relationship between it and the I-PD Control proposed by Kitamari, as well as Optimal Control with some specific equations. We also give the stability analysis with Lyapunov theorem. On this way, we can design a Fuzzy I-PD Controller (FIC) very easier and more effective. Then, preview control element design methodology of FCP was given according to IPC and OPC. Third, to make the system more rapidly and more little overshooting, two factors are given to adjust the controller's properties. At last, the performance of FPC is revealed via computer simulation using a nonlinear plant.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.119-121
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• 1997

This paper suggests a design method of the robust model following PD control system using genetic algorithm. This PD control system is designed by applying genetic algorithm with reference model to the optimal determination of proportional and derivative gains that are given by PD servo controller. These proportional and derivative gains are optimized simultaneously in the search domain guaranteeing the robust stability of closed-loop system satisfying different stability margins. The effectiveness of this PD control system is verified by computer simulation.

• Journal of Advanced Marine Engineering and Technology
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• v.10 no.1
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• pp.51-64
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• 1986

Recently, being due to development of a small microprocessor, microprocessor have found increasing application as a digital controller in the control system. In this paper, authors analyze theoretically the continuous PID controller of a position control system with servomotor, and program the microprocessor as digital PID controller by an assembly language, and search the optimal parameters of the digital PID controller which make the smallest integral square error criterion for a performance criterion, and take experiment the indicial responses with optimal parameter. The results are following. 1) PD- behavior controller was better than P-behavior controller. 2) The smaller the smapling times of P-behavior controller and PD-behavior controller were, the better the indicial responses of the discrete system were. 3) Using a small microprocessor could replace the traditional continuous PID controller for good control.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.3
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• pp.186-193
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• 1988

A pointwise PD-optimal control method is proposed for the continuous path control of robot manipulators with bounded inputs. The controller employs the desired acceleration plus PD (proportional and derivative) actions in the Cartesian space. The gain parameters of the controller are adjusted so that the Euclidean norm of the deviation between the actual and desired accelerations is minimized subject to the constraints of bounded input torques and the system guarantees negative feedback. To show the Validities of the proposed mithods, computer simulations are performed for a SCARA type robot.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.2
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• pp.38-44
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• 1994

Control Algorithms of the Auto-Pilot system have been studied for the navigational economics and crew's comfortability since 1960's, when Auto-Pilot system was installed on the trans-ocean ships. At the beginning the PD control algorithm was used with the weather adjust function introduced to reduce the response of the auto-pilot system to the high frequency wave excitation in rough sea. In this study, the optimal and adaptive control theories are applied for the auto-pilot control algorithm. And those two algorithms are compared through the pre-defined cost function to obtain the most effective control technique for the Auto-Pilot system. The parameterization of the ship meneuvering equation for the adaptive control algorithm design procedure was examined and the advantage of the adaptive control was found through the simulation result with the wrong initial parameter value.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.1-8
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• 2008

A two-wheel balancing vehicle, which helps people moving freely and fast, and is applied from inverted pendulum system, has been widely researched and developed, and some products are came into a market in actuality. Until now, the two-wheel balancing vehicles developed have chosen the general PID control method. In this paper, we propose a new control method to improve a control capacity for a two-wheeled balancing vehicle for human transportation. The proposed method is the fuzzy PD+I control that is one of the improved PID control, and it contains a 2input-1output fuzzy system. This fuzzy system processes signals from proportional and derivative controller, and the fuzzy output signal generates the final output by summing up integral signal. The non-linearity of the fuzzy system makes an optimal output control signal by changing weight of the proportional signal and the derivative signal in process of time. We have simulated the fuzzy PD+I control system and experimented by implementing the two-wheel balancing mobile robot to verify the advantages of the proposed fuzzy PD+I control method in comparison with general PID control. As the results of simulation and experimentation, the proposed fuzzy PD+I control method has better control performance than general PID in this system and improves it.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.201-201
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• 2000

Recently in the design of fuel tanks(launch vehicle, ship, automobile) which transport a large amount of liquid in the cargo holds, the structural damage due to liquid-sloshing becomes an important problem. The impact pressure from sloshing is most violent when the liquid motion of a partially filled tank is in resonance with the motion of a system. In this paper, the sloshing natural periods in liquid tanks are estimated for partially filled tanks with various geometries. In addition to, controlled for a launch vehicle with liquid sloshing effect by PD controller and sloshing filter The PD gain and sloshing filter parameter arc determined by optimal algorithm.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.4
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• pp.43-53
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• 2002

Polishing a die that has free-form surfaces is a time-consuming and tedious job, and requires a considerable amount of high-precision skill. In order to reduce the polishing time and cope with the shortage of skilled workers, a user-friendly automatic polishing system was developed. The polishing system is composed of two subsystems, a three-axis machining center and a two-axis polishing robot. The system has five degrees of freedom and is able to keep the polishing tool in a position normal to the die surface during operation. A sliding mode control algorithm with velocity compensation was proposed to reduce tracking errors. Trajectory tracking experiments showed that the tracking error can be reduced prominently by the proposed sliding mode control compared to a PD (proportional derivative) control. To evaluate the polishing performance of the polishing system and to and the optimal polishing conditions, the polishing experiments were conducted.