• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.785-791
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• 2008

This paper considers the problem of robust $H_{\infty}$ control for uncertain 2-D discrete systems in the General Model via output feedback controllers. The parameter uncertainty is assumed to be norm-bounded. The purpose is the design of output feedback controllers such that the closed-loop system is stable while satisfying a prescribed $H_{\infty}$ performance level. In terms of a linear matrix inequality, a sufficient condition for the solvability of the problem is obtained, and an explicit expression of desired output feedback controllers is given. An example is provided to demonstrate the application of the proposed method.

• IE interfaces
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• v.15 no.2
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• pp.189-198
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• 2002

Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.89-96
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• 1997

A robust speed control scheme for a brushless DC(BLDC) motor using an adaptive input-output linearization technique is presented. By using this technique, the nonlinear motor model can be linearized in Brunovski canonical form, and the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory and positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative experiments.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2477-2479
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• 2005

A robust bending frequency tracker is proposed to design the adaptive notch filter which removes the time-varying missile structural modes from the sensor measurements. To do this, the state-space form of a bending frequency model is derived under the assumption that the bending signal could be described as the lightly damped sinusoid. Since the resultant bending frequency model contains the parametric uncertainties in the measurement matrix, the design problem of bending frequency tracker is tackled by applying the robust Kalman filter to the model. This technique could be easily expanded to the multiple frequencies case because it newly illuminates the bending frequency tracking problem in view of general state estimation.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.223-226
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• 1998

The control objective of steam generator water level in the secondary circuit of a nuclear power plant is to regulate the water level at the desired set point. The dynamics of steam generators is non-linear in nature. The task of modelling such plant is very difficult and especially so when plant operating conditions change frequently. In these reasons, conventional PI gains over all pover range will not work efficiently and a manual control is generally used in low power operation. Therefore the robust H$\infty$ controller design method should be required. In this paper, we design the robust H$\infty$ controller for water level control of steam generator using a mixed H$\infty$ optimization with model-matching method. Firstly we choose the desired model that has good disturbance rejection performance. Secondly we design a stabilizing controller to keep the model-matching error small and also provide sufficiently large stability margin against additive perturbations of the nominal plant.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1029-1031
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• 1999

This paper presents an $H_{\infty}$ based robust STATCOM supplementary controller design to suppress the SSR in series-compensated line. This controller is designed to have the robust stability against the plant model uncertainty. Time domain simulations using a nonlinear system model show that the proposed STATCOM supplementary controller can suppress the SSR efficiently against the plant model uncertainty

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.2
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• pp.157-163
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• 2014

In this paper, a robust MRAC (model reference adaptive control) scheme is applied to control an electrohydraulic positioning system under various loads. The inverse dead-zone compensator in the control system cancels out the dead-zone response, and an integrator added to the controller provides good position-tracking ability. LQG/LTR (linear quadratic Gaussian control with loop transfer recovery) closed-loop model is used as the reference model for learning the MRAC system. LQG/LTR provides a systematic technique to design the linear controller that optimizes the objective function using some compromise between the control effort and the system performance in the frequency domain. Different external load tests are performed to investigate the effectiveness of the designed MRAC system in real time. The experimental results show that the tracking performance of the proposed system is highly accurate, which offers considerable robustness even with a large change in the load.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2484-2491
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• 2009

This paper proposes robust state feedback control of asynchronous sequential machines with model uncertainty. The considered asynchronous machine is deterministic, but its state transition function is partially known before executing a control process. The main objective is to derive the existence condition for a corrective controller for which the behavior of the closed-loop system can match a prescribed model in spite of uncertain transitions. The proposed control scheme also has learning ability. The controller perceives true state transitions as it undergoes corrective actions and reflects the learned knowledge in the next step. An adaptation is made such that the controller can have the minimum number of state transitions to realize a model matching procedure. To demonstrate control construction and execution, a VHDL and FPGA implementation of the proposed control scheme is presented.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.113-122
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• 1997

An adaptive input-output linearization technique for a robust speed control of a brushless C(BLDC) motor is presented. By using this technique, the nonlinear moro model can be effectively linearized in Brunovski canonical form, an the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions caused by the incomplete linearization. for the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory nd positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative simualtions and experiments.