• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.1-8
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• 1997

In order to reject the steady-state tracking error, it is common to introduce integral compensators in servosystems for constant reference signals. However, if the mathematical model of the plant is exact and no disturbance input exists, the integral compensation is not necessary. From this point of view, a two-degree-of-freedom(2DOF) servosystem has been proposed, in which the integral compensation is effective only when there is a modeling error or a disturbance input. The present paper considers robust stability of this 2DOF servosystem incorporating an observer to the structured and unstructured uncertainties of the controlled plant. A robust stability condition is obtained using Riccati inequality, which is written in a linear matrix inequality (LMI) and independent of the gain of the integral compensator. This result impies that if the plant uncertainty is in the allowable set defined by the LMI condition, a high-gain integral compensation can be carried preserving robust stability to accelerate the tracking response.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1255-1263
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• 2015

In the previous work, the authors studied the problem of robust discretization of linear time-invariant systems with polytopic uncertainties, where linear matrix inequality (LMI) conditions were developed to find an approximate discrete-time (DT) model of a continuous-time (CT) system with uncertainties in polytopic domain. The system matrices of obtained DT model preserved the polytopic structures of the original CT system. In this paper, we extend the previous approach to solve the problem of robust discretization of polytopic uncertain systems with aperiodic sampling. In contrast with the previous work, the sampling period is assumed to be unknown, time-varying, but contained within a known interval. The solution procedures are presented in terms of unidimensional optimizations subject to LMI constraints which are numerically tractable via LMI solvers. Finally, an example is given to show the validity of the proposed techniques.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.724-732
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• 2016

In this paper, a sampled-data observer-based decentralized fuzzy control technique is proposed for a class of nonlinear large-scale systems, which can be represented to a Takagi-Sugeno fuzzy system. The premise variable is assumed to be measurable for the design of the observer-based fuzzy controller, and the closed-loop system is obtained. Based on an exact discretized model of the closed-loop system, the stability condition is derived for the closed-loop system. Also, the stability condition is converted into the linear matrix inequality (LMI) format. Finally, an example is provided to verify the effectiveness of the proposed techniques.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.6
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• pp.538-548
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• 2014

This study provides a robust control of a grid-connected three-phase two-level photo voltaic inverter. The introduced control method uses the cascade control strategy to regulate AC-side current and DC-link voltage. A robust controller with integration action is used for the inner-loop AC-side current control, which maximizes the convergence rate using a linear matrix inequality-based optimization design method and eliminates the offset error. The robust controller design method considers the parameter uncertainty set to accommodate parameter mismatch and un-modeled components in the inverter model. An outer-loop proportional-integral controller is used to regulate DC-link voltage with linearization of DC/AC relation. The proposed control strategy is applied to a grid-connected 100 kW photo voltaic inverter.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.12
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• pp.655-660
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• 2004

This paper deals with the design of a fixed-structure $H_\infty$ power system stabilizer (PSS) by using an iterative linear matrix inequality (LMI) method. The fixed-structure $H_\infty$ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, a linear penalty function is incorporated into the objective function so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Numerical experiments show the practical applicability of the proposed algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.187-193
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• 2003

In this paper, a systematic design method of the intelligent PAM fuzzy controller for nonlinear systems using the efficient tools-Linear Matrix Inequality and the intelligent digital redesign is proposed. In order to digitally control the nonlinear systems, the TS fuzzy model is used for fuzzy modeling of the given nonlinear system. The convex representation technique also can be utilized for obtaining TS fuzzy models. First, the analog fuzzy-model-based controller is designed such that the closed-loop system is globally asymptotically stable in the sense of Lyapunov stability criterion. The simulation results strongly convince us that the proposed method has great potential in the application to the industry.

• Journal of Preventive Medicine and Public Health
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• v.40 no.6
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• pp.419-421
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• 2007

Objectives : The aim of this study was to introduce the concept of health inequalities, and to discuss the underlying assumptions and ethical backgrounds associated with the issue, as well as the theoretical and practical implications of health inequalities. Methods : Based on a review of the literature, we summarize the concepts of health inequalities and inequities and discuss the underlying assumptions and ethical backgrounds associated with these issues from the view of social justice theory. We then discuss the theoretical and practical implications of health inequalities. Results : Health inequality involves ethical considerations, such as judgments on fairness, and it could provide a sensitive barometer to reflect the fairness of social arrangements. Discussion on health inequalities could deepen our understanding of the social etiology of health and provide a basis for the development of comprehensive and integrative social policies. Conclusions : Health equity is not a social goal in and of itself, but should be considered as a part of a broader effort to seek social justice.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.279-283
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• 2005

This paper deals with the design of a low-order H/sub ∞/ controller by using an iterative linear matrix inequality (LMI) method. The low-order H/sub ∞/ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, the recently developed penalty function method is applied. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. Numerical experiments showed the effectiveness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.656-661
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• 2005

This paper is concerned with an iterative linear matrix inequality (LMI) approach to the design of a structurally constrained output feedback controller such as decentralized control. The structured synthesis is formulated as a novel rank-constrained LMI optimization problem, where the controller parameters are explicitly described so as to impose structural constraints on the parameter matrices. An iterative penalty method is applied to solve the rank-constrained LMI problem. Numerical experiments are performed to illustrate the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.517-523
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• 2006

This paper is focused on a robust saturation controller for the stable linear time-invariant (LTI) system involving both actuator's saturation and structured real parameter uncertainties. Based on affine quadratic stability and multi-convexity concept, a robust saturation controller is newly proposed and the linear matrix inequality (LMI)-based sufficient existence conditions for this controller are presented. The controller suggested in this paper can analytically prescribe the lower and upper bounds of parameter uncertainties, and guarantee the closed-loop robust stability of the system in the presence of actuator's saturation. Through numerical simulations, it is confirmed that the proposed robust saturation controller is robustly stable with respect to parameter uncertainties over the prescribed range defined by the lower and upper bounds.