• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.27.3-27
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• 2001

In this paper, a robust receding horizon controller for uncertain linear time-varying systems is presented in the dynamic output-feedback form. The existing output-feedback receding horizon controller in the literature is composed of a state observer and a static controller associated with the observer states (similar to LQC control), where the fundamental assumption is that the state observer will supply the exact states as time goes up. The performance of those controllers may be much degraded and even the closed-loop stability may not be guaranteed when the system suffers from disturbances and uncertainties or is time-varying. The proposed controller, which is not necessary to have the state-observer, overcomes such difficulties. Using matrix inequality conditions on the terminal weighting matrix, the closed-loop system stability is guaranteed. Numerical examples are ...

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2189-2196
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• 2016

This paper proposes a new finite control set-model predictive control (FCS-MPC) method for induction motors. In the method, the reference state that satisfies the given torque and rotor flux requirements is derived. Cost indices for the FCS-MPC are defined using the state tracking error, and a linear matrix inequality is formulated to obtain a proper weighting matrix for the state tracking error. The on-line procedure of the proposed FCS-MPC comprises of two steps: select the output voltage vector of the two level inverter minimizing the cost index and compute the optimal modulation factor of the minimizing output voltage vector in order to reduce the state tracking error and torque ripple. The steady state tracking error is removed by using an integrator to adjust the reference state. The simulation and experimental results demonstrated that the proposed FCS-MPC shows good torque, rotor flux control performances at different rotating speeds.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.3
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• pp.299-306
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• 2002

The load frequency control(LFC) of power system is one of important subjects in view of system operation and control. That is, even though the rapid load disturbances are applied to the given power system, the stable and reliable power should be supplied to the users, converging unconditionally and rapidly the frequency deviations and the tie-line power flow ones of each area into allowable boundary limits. Nonetheless of such needs, if the internal parameter perturbation and the sudden load variation are given, the unstable phenomena of power systems can be often brought out because of the large frequency deviation and the unsuppressible power line one. So, an optimal modulation controller for UC of multi-area power system is designed by a recursive algorithm that determines the state weighting matrix Q of a linear quadratic performance criterion. The optimal modulation controller is based on optimal control and can obtain the exact dynamic response of the UC of multi-area power system in the time domain. The performances of the resultant optimal modulation control, that is, the steady-state deviations of frequency and tie-line power flow and the related dynamics, were investigated and analyzed in detail by being applied to the UC of multi-area power system in the perturbations of predetermined internal parameters. Through the simulation results tried variously in this paper for disturbance of stepwise load changes, the superiorities of the proposed optimal modulation controller in robustness and stability were proved.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1744-1746
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• 2004

This paper focuses on the problem of asymptotic stabilization for time-delay systems. To this end, a memoryless state feedback controller is proposed. Then, based on the Lyapunov method, a delay-dependent stabilization criterion is devised by taking the relationship between the terms in the Leibniz-Newton formula into account. Certain free weighting matrices are used to express this relationship and linear matrix inequalities (LMIs)-based algorithm to design the controller stabilizing the system.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.215-219
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• 1991

This paper is equivalent model transform which reduces the restriction of digitalization in the discrete linear system. This algorithm is the method that weight is given to contribillity and obserbility gramian, the regular matrix T of coordinate transform is obtained and then the state space coefficents of weighted model can be obtained. This study shows the frequency reponse of low quantization error according to the order of weighting function. The result shows that frequency response of the proposed algorithm is better than that of the balanced realization in the system of smaller bit.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.280-288
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• 1998

In this paper, a novel relation between the weighting matrix Q in LQR and the eigenstructure of the desired closed-loop system is proposed. Thus, the state feedback gain with the desired eigenstructure in the LQR can be obtained. The proposed scheme is applied to design a simple 3rd-order system and a flight control system design to show the usefulness of the scheme.

• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.119-120
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• 1979

A linear state equation of the first order differential form relating the load-frequency dynamic characteristics of interconnected power systems was derived for use in computer simulation. A now solution of the algebraic matrix riccati equation for application in quadratic optimal controllor and least-square state estimator dermination was developed. The program for a dynamic state equation for two interconnected control areas was developed. The optimized load-frequency deviation was analysed and a numerical analysis was tried based on the computer simulation. It was shown that the dynamic response of th loed-frequency could be optimized with weighting factors IR and Q. The result was that the load-frequency and the tie-line deviation were visibly reduced.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.373-380
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• 2001

In this research, a controller design method based on optimization is proposed that can satisfy constraints on maximum responses of building structures subject to ground excitation modeled by partially stationary stochastic process. The class of controllers to be optimized is restricted to LQR. Weighting matrix on controlled outputs is used as design variable. Objective function constraint functions and their gradients are computed parameterizing control gain with Riccati matrix. Full state feedback controllers designed by Proposed optimization method satisfy various design objectives and their necessary maximum control forces are computed fur the production of actuator. Probabilities of maximum responses match statistical data from simulation results well.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.3
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• pp.172-179
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• 2003

Linear matrix Inequality based $H_\infty$ robust controller is designed to control the motion of a 4-axis unbalanced rigid asymmetric rotor supported and controlled by two active magnetic bearings in this paper. To this end, the equations of motion of the system are derived via Hamilton's variational principle and transformed to a state-space form for the standard $H_\infty$ control problem. LMI-based controller, which does not require additional assumptions beyond the usual stabilizability and detectability assumptions, is designed based upon the pole place weighting function and loopshaping technique. The obtained results are compared with those reported in the available literature and the efficiency of the proposed LMI-based $H_\infty$ control is revealed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.797-802
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• 2010

In this paper, a systematic procedure to design a nonlinear controller for nonlinear active magnetic bearing (AMB) systems is presented. To do this, we effectively convert the AMB system into a polytopic quasi-linear parameter varying (LPV) system, which is a representation of nonlinear state-space models and is described by the convex combination of a set of precisely known vertices. Unlike the existing quasi-LPV systems, the nonlinear weighting functions, which construct the polytopic quasi-LPV model of the AMB system by connecting the vertices, include not only state variables but also the input ones. This allows us to treat the input nonlinearity effectively. By means of the derived polytopic quasi-LPV model and linear matrix inequality (LMI) conditions, nonlinear controller that stabilizes the AMB system is obtained. The effectiveness of the proposed controller design methodology is finally demonstrated through numerical simulations.