• Journal of KSNVE
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• v.11 no.1
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• pp.49-56
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• 2001

In this paper, two plant models, of which one is newly developed and the other one is the conventional one, of the focus servo system of DVD drive are presented and a two-degree-of freedom controller consisted of Inverse dynamics feedforward and LQG/LTR feedback controller is designed. The newly developed plant model is used to design the feedforward controller and the conventional model is used for the design of feedback controller. The output of newly developed model is the displacement of objective lens and the output of conventional model is the focus error of the DVD focus servo system. The displacement of the objective lens is estimated by the dynamics model of the DVD focus servo system. The disturbance rejection performance of the two-degree-of freedom controller is compared with that of an LQG/LTR one.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.221-226
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• 2006

In this paper, we study an approach to design a Fuzzy PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of traditional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. In order to solve the above problems, we adapt Fuzzy PI controller for the fire angle control of rectifier. The performance of the Fuzzy PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain factors of the Fuzzy PI controller by Genetic Algorithms. A comparative study has been performed between Fuzzy PI controller and traditional PI controller, to prove the superiority of the proposed scheme.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.157-160
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• 2001

This paper presents A Design of WMR Controller that being composed of cooperative relation between PID controller and optimized neural network algorithm, it operate a variable control by velocity. Some proposed algorithm in the past just depended on PID controller for the control of position of WMR but for more efficient control we design a variable controller that operate control by PD controller using neural network if it is satisfied with any given condition. it adjust gain of PD controller for real time control using a fast feedforward algorithm which is different with Form of the standard backpropagation algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.3-75
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• 2001

This paper addresses the design of State-feedback Robust Guaranteed-Cost Controllers with controller gain variations. Since the unstructured uncertainty is the most dominant uncertainty in the modeling of the plant, the plant is assumed to have the unstructured uncertainty. It is necessary to take the controller parameter perturbation into consideration when we design the robust controller. Otherwise, the resulting controller may show the fragility property. That is to say, the extremely small controller parameter variation may result in the instability of the overall closed-loop system. Therefore, the design purpose is that the maximum performance index is guaranteed in the presence of the unstructured plant uncertainty and controller parameter variations ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.180.5-180
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• 2001

This paper presents A Design of WMR Controller that being composed of cooperative relation between PID controller and optimized neural network algorithm, it operate a variable control by velocity. Some proposed algorithm in the past just depended on PID controller for the control of position of WMR but for more efficient control we design a variable controller that operate control by PD controller using neural network if it is satisfied with any given condition. it adjust gain of PD controller for real time control using a fast feedforward algorithm which is different with Form of the standard backpropagation algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.6
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• pp.509-517
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• 2001

To deal with non-linearities and time-varying characteristics of hydraulic systems, in this paper, the neuro-fuzzy controller has been introduced. This controller does not require and accurate mathematical model for the nonlinear factor. In order to solve general fuzzy inference problems, the input membership function and fuzzy reasoning rules are used for determining the controller parameters. These parameters are determined by using the learning algorithm. The control performance of the neuro-fuzzy controller is evaluated through a series of experiments for the various types of inputs while applying disturbances to the hydraulic system. The performance of this controller was compared with those of PID and PD controllers. From these results, We observe be said that the position tracking performance of neuro-fuzzy is better those of PID and PD controllers.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.104-106
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• 2007

In this paper, we propose an approach to design of optimized Cascade controller for Rotary Inverted Pendulum system using Hierarchical Fair Competition-based Genetic Algorithm(HFCGA). GAs may get trapped in a sub-optimal region of the search space thus becoming unable to find better quality solutions, especially for very large search space. The Parallel Genetic Algorithms(PGA) are developed with the aid of global search and retard premature convergence. HFCGA is a kind of multi-populations of PGA. In this paper, we design optimized Cascade controller by HFCGA for Rotary Inverted Pendulum system that is nonlinear and unstable. Cascade controller comprise two feedback loop, parameters of controller optimize using HFCGA. Then designed controller evaluate by apply to the real plant.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.17-26
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• 2002

In this paper, a new design methodology of the fuzzy controller is presented. The performance of the fuzzy controller is sensitive to the variety of scaling factors. The design procedure is based on evolutionary computing (more specifically, a genetic algorithm) and estimation algorithm to adjust and estimate scaling factors respectively. The tuning of the soiling factors of the fuzzy controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy controller by means of two types of estimation algorithms such as HCM (Hard C-Means) and Neuro-Fuzzy model[7]. The validity and effectiveness of the proposed estimation algorithm for the fuzzy controller are demonstrated by the inverted pendulum system.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.355-367
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• 2007

This paper proposes a design method of the PI(Proportional-Integral)+D(Derivative) controller using self-tuning of the design variables and controller gains. The used fuzzy PI+D controller is the approximated conventional continuos time linear PI+D controller and the used fuzzification method is the fuzzy single tone and the adapted defuzzification method is the simplified tenter of gravity. Fuzzy estimation result would be calculated in the other function elements from the classified fuzzy variables and the result determined by the design variables decides the controller gains. As a result, the proposed method shows the capability of the high speed tuning and can be applied to the case of input variables with many fuzzy partitions and also can bring out the advantage to reduce the reconstruction(digital sampling reconstruction) error. Most simulation results show that this controller makes much bettor efficiency and improvement by using design variables and controller gains.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.2 s.344
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• pp.96-104
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• 2006

This paper presents design methodology, encient verification and implementation of a CAN protocol controller. The design methodology uses a heuristic technique to make the design flexible and cost effective. Using the design methodology, we created architecture for a CAN controller which has flexible and low cost features. For faster time-to-market and reliable operation of the designed CAN protocol controller, we p개posed a three-step verification process which uses three different kinds of verification techniques. The goal of this three-step verification is to reduce the number of test sequences in order to rapidly implement the design without loss of reliability for faster time-to-market. The designed CAN protocol controller was fabricated using a 0.35 micrometer CMOS technology.