• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.2-75
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• 2001

In this paper, we provide the technique of H$\infty$ controller design algorithm for input-saturated linear systems using a linear parameter varying(LPV) framework. The LPV controller with parameter dependent dynamic state feedback controller concept guarantees the asymtotic stability and H$\infty$ norm bound within prescribed level v using the saturation nonlinearity as scheduling parameters. Especially, the sufficient conditions for the existence of H$\infty$ controller are formulated in terms of linear matrix inequalities(LMIs) that can be solved very efficiently.

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.1209-1212
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• 2003

In this paper, we propose a SDRAM Controller. The SDRAM is often used a mainstream memory as embedded system memory due to its short latency, burst access and pipeline features. The proposed Controller provides essential functions for SDRAM initialization, read/write accesses, memory refresh and Burst access. Furthermore, the proposed controller is implemented in the form of SOFT IP. Therefore, it reduces the designer's effort greatly.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.246-248
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• 2006

This paper is concerned with non-fragile guaranteed cost state feedback controller design algorithm for descriptor systems with time-varying delay and static state feedback controller with multiplicative uncertainty. The considered uncertainties are norm-bounded and time delay is time-varying. Under the condition of controller gain variations, conditions for the existence of controller satisfying asymptotic stability and non-fragility and controller design method are derived via LMI approach. Moreover, the measure of non-fragility and the upper bound to minimize guaranteed cost function are given.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.474-476
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• 1998

In this paper, a multi variable neuro-fuzzy controller for a boiler-turbine system is designed. Two architectures are used. The first consists of boiler-turbine system identification and the second is designing a controller. A generalized backpropagation algorithm is developed and used to train the neuro-fuzzy controller. Designed controller is good tracking property and rejects the input and output disturbances. The results of the proposed design method is verified through simulation.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.732-734
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• 1997

This paper describes the design and implementation of a fuzzy temperature control system to control the water temperature in plant. For evaluating the performance of a fuzzy controller, the experiment results of a fuzzy controller are compared with these of a conventional PID controller which provides an auto-tuning function. The experiment results show that the proposed controller has a good control performance and is robust to external disturbance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.43-46
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• 2001

We, in this paper, design the Sugeno-models fuzzy controller by using the membership function modification algorithm and ANFIS, which are clustering and learning the input-output data. The membership function modification algorithm constructs the more concrete fuzzy controller by clustering the input-output data from the fuzzy inference system. ANFIS construct the Sugeno-models fuzzy controller by learning the input-output data from the above controller. We showed that the fuzzy controller designed by our method could have the stable learning and the enhanced performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.303-311
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• 2012

In this study, we introduce a dynamic process model as well as the design methodology of optimized fuzzy controller for its efficient application to vacuum production system to produce a semiconductor, solar module and display and so on. In a vacuum control field, PID control method is widely used from the viewpoint of simple structure and preferred performance. But, PID control method is very sensitive to the change of environment of control system as well as the change of control parameters. Therefore, it's difficult to get a preferred performance results from target system which has a complicated structure and lots of nonlinear factors. To solve such problem, we propose the design methodology of an optimized fuzzy PID controller through a following series of steps. First a dynamic characteristic of the target system is analyzed through a series of experiments. Second the process model is built up and its characteristic is compared with real process. Third, the optimized fuzzy PID controller is designed using genetic algorithms. Finally, the fuzzy controller is applied to target system and then its performance is compared with that of other conventional controllers(PID, PI, and Fuzzy PI controller). The performance of the proposed fuzzy controller is evaluated in terms of auto-tuned control parameters and output responses considered by ITAE index, overshoot, rise time and steady state time.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.5
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• pp.1-7
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• 2008

This paper presents not only the robust stabilization technique but also robust non-fragile controller design method for discrete-time singular systems and static state feedback controller with multiplicative uncertainty. The condition for the existence of robust stabilization controller, the admissible controller design method, and the measure of non-fragility in controller are proposed via LMI(linear matrix inequality) approach. In order to get the maximum measure of non-fragility, the obtained sufficient condition can be rewritten as LMI optimization form in terms of transformed variable. Therefore, the presented robust non-fragile controller for discrete-time singular systems guarantees robust stability in spite of parameter uncertainty and controller fragility. Finally, a numerical example is given to show the validity of the design method.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.2
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• pp.183-190
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• 2007

In this paper, a robust controller for PWM converter is proposed. The proposde converter controller consists of a PI controller for DC output voltage and a current controller using error-space approach for maintaining the sinusoidal current waveform and unity power factor. Conventionally, the try and error method has been used to design the current controller considering the switching frequency of the devices and sampling frequency of the digital controller. But this proposed method is based on characteristic ratio assignment(CRA) method which has the advantage to design the optimal gain to meet the referenced response and overshoot within the limit range. First, the CRA based current controller algorithm is explained. Then the validity of proposed controller is verified through the PSiM simulation and experience results.

• Journal of Mechanical Science and Technology
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• v.16 no.12
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• pp.1583-1593
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• 2002

This paper discusses the model validation and vibration suppression of an AMB flexible rotor via additional LQG controller. The main difficulty in the vibration suppression of the flexible rotor using AMB is to realize a controller that can minimize resonance without injuring the stabilized rigid modes. In order to solve this problem, simple scheme for system modeling and controller design are developed. Firstly, the AMB flexible rotor is stabilized with a PID controller, which leads to a new stable rotor-bearing system. Then, authors propose the model validation procedure using measured open-loop frequency responses to obtain an accurate model of the AMB flexible rotor system. After that, LQG controller with modal weighting is designed to suppress resonances of the stable rotor-bearing system. Due to the poor controllability and observability of flexible modes compared to rigid ones, balancing of two Gramians is prerequisite for the fair LQG controller design. Simulation with step disturbance and experimental results of unbalance response up to 10,000 rpm verified the effectiveness of the proposed scheme.