• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.526-530
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• 2011

This paper presents a new fuzzy model-based design approach for waypoints-tracking control of nonlinear underwater vehicles (UUVs) on a horizontal plane. The waypoints-tracking control problem is converted into the stabilization one for the error model between the given nonlinear UUV and the waypoints. By using the sector nonlinearity, the error model is modeled in Takagi-Sugeno's form. We then derive stabilization conditions for the error model in the format of linear matrix inequality. A numerical simulation is provided to illustrate the effectiveness of the proposed methodology.

• 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.

• Bulletin of the Korean Mathematical Society
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• v.57 no.3
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• pp.583-595
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• 2020

Let HE_I, HE_II, HE_III and HE_IV be the first, second, third and fourth type Loo-Keng Hua domain respectively, 𝜑 a holomorphic self-map of HE_I, HE_II, HE_III, or HE_IV and u ∈ H(𝓜) the space of all holomorphic functions on 𝓜 ∈ {HE_I, HE_II, HE_III, HE_IV}. In this paper, motivated by the well known Hua's matrix inequality, first some inequalities for the points in the Bers-type spaces of the Loo-Keng Hua domains are obtained, and then the boundedness and compactness of the weighted composition operators W_𝜑,u : f ↦ u · f ◦ 𝜑 on Bers-type spaces of these domains are characterized.

• 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 Mechanical Science and Technology
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• v.19 no.5
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• pp.1138-1147
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• 2005

This paper aims at demonstrating the feasibility of active control of beams with a multiobjective state-feedback control technique. The multiobjective state-feedback controller is de­signed on a linear matrix inequality (LMI) approach for the multiobjective synthesis. The design objectives are to achieve a mix of Hoo performance and H2 performance satisfying constraints on the closed-loop pole locations in the face of model uncertainties. The controller is also designed to reject the effects of the noise and external of disturbances. For the theoretical analysis, the governing equation of motion is derived by Hamilton's principle to describe the dynamics of a smart structural system. Numerical examples are presented to demonstrate the effectiveness of the integrated robust controller in damping out the multiple vibration modes of the piezo/beam system.

• Journal of Power System Engineering
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• v.4 no.4
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• pp.84-91
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• 2000

This paper describes a state feedback controller design method of the integral type magnetic levitation servo system which satisfies the design objectives. The design objective is a $H_{\infty}$ performance, asymptotic disturbance rejection and a robust pole assignment in linear matrix inequality(LMI) region. To the end, we investigated the validity of the designed controller which considering a robust pole assignment region, through results of simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.10 s.253
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• pp.1249-1254
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• 2006

Existing adaptive observers may cause the parameter drifts due to disturbances even if state estimation errors remain small. To avoid the drift phenomena in the presence of bounded disturbances, several robust adaptive observers have been introduced addressing bounds in state and parameter estimates. However, it is not easy for these observers to manipulate the size of the bounds with the selection of the observer gain. In order to reduce estimation errors, this paper introduces the (equation omitted) gain minimization problem in the adaptive observer structure, which minimizes the (equation omitted) gain between disturbances and estimation errors. The stability condition of the adaptive observer is reformulated as a linear matrix inequality, and the observer gain is optimally chosen by solving the convex optimization problem. The estimation performance is demonstrated through a numerical example.