• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.846-852
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• 2013

In this paper, the authors propose a new approach to control problem of the marine vessels which are moored or controlled by actuators. The vessel control problem in the specified area is called a DPS (Dynamic Positioning System). The main objective of this paper is to obtain more useful control design method for DPS. In this problem, a complicate fact is control allocation which is a numerical method for distributing the control signal to the controlled system. For this, many results have been given and verified by other researchers using two individual processes. It means that the controller design and control allocation design process are carried out individually. In this paper, the authors give more sophisticated design solution on this issue. In which the controller design and control allocation problem are unified by a robust controller design problem. In other word, the stability of the closed-loop system, control performance and allocation problem are unified by an LMI (Linear Matrix Inequality) constraint based on $H_2/H_{\infty}$ mixed design framework. The usefulness of proposed approach is verified by simulation with a supply vessel model and found works well.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.997_998
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• 2009

Nowadays DC-DC converter has been used widely in electronic production. It has a high requirement in wide input voltage, load variations, stability, providing a fast transient response and the most important thing is that it can be applied easily and efficiently. However, it is not easy to be controlled because of nonlinear system. This study introduces a fuzzy linear control design method for nonlinear systems with optimal $H^{\infty}$ robustness performance. First, the Takagi and Sugeno fuzzy linear model is employed to approximate a nonlinear system. Next, based on the fuzzy linear model, a fuzzy controller is developed to stabilize the nonlinear system, and at the same time the effect of external disturbance on control performance is attenuated to a minimum level. Thus based on the fuzzy linear model, ��$H^{\infty}$ performance design can be achieved in nonlinear control systems. Linear matrix inequality (LMI) techniques are employed to solve this robust fuzzy control problem. PI control structure is used and the control gains are determined based on $H^{\infty}$ control.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.483-490
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• 2004

The descriptor system model has a high ability in representing dynamical systems. It can preserve physical parameters in the coefficient matrices, and describe the dynamic part, static part, and even the improper part of the system in the same form. The design of mixed $H_{2}/H_{\infty}$ controllers for linear time-invariant descriptor systems is considered in this paper. Firstly, an $H_2$ and $H_{\infty}$ synthesis problems fur a descriptor system are presented separately in terms of linear matrix inequalities (LMIs) based on the bounded real lemma. Then, we show that the existence of a mixed $H_2/H_{\infty}$ controller by which the $H_2$ norm of the second channel is minimized while keeping the $H_2$ norm bound of the first channel less than ${\gamma}$, is reduced to the linear objective minimization problem. The class of desired controllers that are assumed to have the same structure as the plant is parameterized by using the linearizing change of variables.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1973-1975
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• 2001

In this paper, we consider the problem of robust peak-to-peak controller design of linear system. The goal is to design a controller which minimizes the maximum peak value of the measured output subjects to the peak bounded disturbance. The control is obtained by checking the feasibility of the derived matrix inequalities. Finally, we shows the usefulness of our result comparing to $H_{\infty}$ and $H_{2}$ control by an example.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.144-153
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• 1996

The magnetic levitation system has many advantages, such as little friction, no lubrication, no noise and so on. For this reason, the magnetic levitation system is utilized in the magnetic bearing of high-speed rotor. The method to obtain magnetic force is both the repulsive suspension method and the attraction suspension method need a stabilizing controller because it is a unstable system in natural. This paper presents the design of robust stabilizing servo controller in spite of being the model uncertainties in the magnetic levitation system by $\textit{H}_{\infty}$ control theory using the free parameter. And we investigated the validity of a designed controller through results of the simulation and the actual experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.102-108
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• 2001

In this paper, an active noise controller for a communication headset was designed. In a communication headset, there exist information signals such as voices from the end for the communication line as well as also, undesirable noises with are induced by external noise sources such as engine noises. Therefore, it is necessary to reduce the external noises for clear hearing of the communication signals. This problem was solved by robust H(sub)$\infty$ controller to reduce noise and a compensator for information signals The designed controller was implemented using TMS320C31 DSP Op-amp, and several experiments were performed to verify its performance. The results showed that the controller reduces the undesirable noises sufficiently, while communication signals are not reduced.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.397-400
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• 1996

In this paper, robust motion control of a flexible micro-actuator is presented. The actuator is made of a bimorph piezoelectric high-polymer material (PVDF). No mathematical model system can exactly model a physical system such a flexible micro-actuator. For this reason we must be aware of how modeling errors might adversely affect the performance of a control system for such a model. The H method addresses a wide range of the control problems, combining the frequency and time domain approaches. The design is an optimal one in the sense of minimization of the maximum of the closed-loop transfer function. It includes colored measurement and process noise. It also addresses the issues of robustness due to model uncertainties, and is applicable to the, flexible micro-actuator control problem. Therefore, we adopt the H control problem to the robust motion control of the flexible micro-actuator. Theoretical and experimental results demonstrate the satisfactory performance and the effectiveness of the designed controller. the effectiveness of the designed controller.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2723-2725
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• 2005

In this paper, a robust $H{\infty}$ stabilization problem to a uncertain discrete-time nonlinear systems with time-delay via fuzzy static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent an uncertain nonlinear systems with time-delayed state. Then parallel distributed compensation technique is used for designing of the robust fuzzy controller. Using a single Lyapunov function, the globally asymptotic stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust $H{\infty}$ controllers are given in terms of linear matrix inequalities via similarity transform and congruence transform technique.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1981-1986
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• 2004

In this study, the basic motor control system had been investigated. The controller for this study consists of two main parts, a feedforward controller part and a feedback controller part. Each part will deals with different control problems. The feedback controller deals with robustness and stability, while the feedforward controller deals with response speed. The feedforward controller, used to solve the tracking control problem, is adaptable. To make such a tracking perfect, an adaptive law based on Feedback Error Learning (FEL) is designed so that the feedforward controller becomes an inverse system of the controlled plant. The novelty of FEL method lies in its use of feedback error as a teaching signal for learning the inverse model. The theory in $H^{\infty}$-Control is selected to be applied in the feedback part to guarantee the stability and solve the robust stabilization problems. The simulation of each individual part and the integrated one are taken to clarify the study.

• Earthquakes and Structures
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• v.10 no.6
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• pp.1253-1272
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• 2016

For a nonlinear control system, there are many uncertainties, such as the structural model, controlled parameters and external loads. Although the significant progress has been achieved on the robust control of nonlinear systems through some researches on this issue, there are still some limitations, for instance, the complicated solving process, weak conservatism of system, involuted structures and high order of controllers. In this study, the computational structural mechanics and optimal control theory are adopted to address above problems. The induced norm is the eigenvalue problem in structural mechanics, i.e., the elastic stable Euler critical force or eigenfrequency of structural system. The segment mixed energy is introduced with a precise integration and an extended Wittrick-Williams (W-W) induced norm calculation method. This is then incorporated in the market-based control (MBC) theory and combined with the force analogy method (FAM) to solve the MBC robust strategy (R-MBC) of nonlinear systems. Finally, a single-degree-of-freedom (SDOF) system and a 9-stories steel frame structure are analyzed. The results are compared with those calculated by the $H{\infty}$-robust (R-$H{\infty}$) algorithm, and show the induced norm leads to the infinite control output as soon as it reaches the critical value. The R-MBC strategy has a better control effect than the R-$H{\infty}$ algorithm and has the advantage of strong strain capacity and short online computation time. Thus, it can be applied to large complex structures.