• Proceedings of the KIEE Conference
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• 1974.01a
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• pp.36-36
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• 1974

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.470-473
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• 1995

There exist two critical in application of the magnetic bearing system. One is the control axis interference caused by gyroscopic effect and the other is the vibration caused by the unbalance on the rotor. To solve both problems at the same time, first, a centralized full-state feedback controller based on the LQR control theory was designed to compensate for the gyroscopic effect. Second, disturbance rejection control input based on the observer was designed to avoid the vibration causer by the unbalanced rotor. Balancing input computer accroding to LQR and output of the observer were derived in term of rotational speed. Effectiveness of the on-line balancing was verified through numerical simulation. The developed observer-based controller was also applied to the linear and nonlinear magnetic bearing systems.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1327-1334
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• 1999

The stabilization control of ball-beam system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of classical methods such as the PID and the full state feedback controller(FSFC) based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Therefore, in this paper, three improved design techniques of stabilization controller for a ball-beam system were proposed. These parameter tuning methods in the double PID controller(DPIDC), the FSFC and the a sliding mode controller(SMC) were dependent upon the Real Value Elitist Genetic Algorithm (RVEGA). Finally, by applying the DPIDC, the FSFC and the Real Variable Elitist Genetic Algorithm based Sliding Mode Control(RVEGA SMC) to the stabilizations of a ball-beam system, the performances of the RVEGA SMC technique were showed to be superior to those of two other type controllers.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.172.2-172
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• 2001

We introduce a new stable feedback controller eventually converges to a conventional SDRE(State Dependent Riccati Equation) based optimal (suboptimal) controller. On conventional SDRE, the optimal control input should be obtained by backward integration of the SDRE at each control point. The proposed controller is given by direct forward integration of a proposed SDRE. This fact enables fast computation and easy implementation. On concerning a state dependent system, the proposed controller may be a candidate to the conventional SDRE based optimal controller if the system is slow varying with states. Though the controller is fast and easy to implement it is not able to cope with a fast varying system. We introduce an optimality index, which indicates how far the proposed controller is deviated from the solution of the convectional SDRE. If the index escapes a ...

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.491-495
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• 2016

We deal with the regulation problem of nonlinear systems with time-varying delays in both the states and input. A new state feedback controller with dynamic gains is developed based on matrix inequality and non-predictor methods. The proposed control scheme is analyzed using the Razumikhin theorem, and its effectiveness is demonstrated with simulation results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2567-2576
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• 1994

In this paper we propose a new method to determine the learning rates of fuzzy learning algorithm(FLA) in nonlinear MIMO system. The state feedback gains are used from the linearized system of the nonlinear MIMO system. Through this method, it is easy to determine the learing rates. And it is quarauteed the good convergence and confirmed the performance of FLA is better than that of linear controller(LC) through the simulation. Acrobatic robot system is selected as an example(one-input two-output system), and FLA is implemented through the experiment.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.76-86
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• 1998

The Two-Mass Spring(TMS or Two-Inertia Resonance) system is one of the simplest models which generate a torsional vibration. In this system, it is required to design a controller achieving the control performance while suppressing the torsional vibration. In this paper, we compared and considered with the state feedback effects for the TMS system. By connecting each controller design to the state feedback control, we could predict each controller performances and decide weighting functions and parameters of LQ and $H_\infty$ controller.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1133-1135
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• 2000

In the industrial motor drive system which is composed of a motor and load connected with a flexible shaft, a torsional vibration is often generated because of the elastic elements in torque transmission. To solve this problem, the two-degrees-of-freedom $H_{\infty}$ controller was designed. But it is difficult to realize that controller. In this paper, a new partial state feedback $H_{\infty}$ controller with resonance ratio control is proposed. Proposed controller has simple structure but satisfies the attenuation of disturbances and vibrations.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.61-76
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• 2002

The robust non-fragile guaranteed cost control problem is studied in this paper for class of uncertain linear large-scale systems with time-varying delays in subsystem interconnections and given quadratic cost functions. The uncertainty in the system is assumed to be norm-hounded arid time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound far all admissible uncertainties. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost contrellers is 7iven in terms of the feasible solution to a certain LMI. Finally, in order to show the application of the proposed method, a numerical example is included.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.3
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• pp.183-190
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• 2002

This paper describes the synthesis of robust and non-fragile H$\infty$ state feedback controllers for linear varying systems with affine parameter uncertainties, and static state feedback controller with structured uncertainty. The sufficient condition of controller existence, the design method of robust and non-fragile H$\infty$ static state feedback controller, and the set of controllers which satisfies non-fragility are presented. The obtained condition can be rewritten as parameterized Linear Matrix Inequalities(PLMls), that is, LMIs whose coefficients are functions of a parameter confined to a compact set. However, in contrast to LMIs, PLMIs feasibility problems involve infinitely many LMIs hence are inherently difficult to solve numerically. Therefore PLMls are transformed into standard LMI problems using relaxation techniques relying on separated convexity concepts. We show that the resulting controller guarantees the asymptotic stability and disturbance attenuation of the closed loop system in spite of controller gain variations within a degree.