• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.291-294
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• 2006

This paper presents a decentralized input-output feedback linearizing controller for a multi-machine power system. Firstly, the controller is designed using input-output feedback linearization for modified outputs. Then we present a guideline for selecting gains of the controller and parameters in the modified outputs. Simulations illustrate the effectiveness of the proposed control scheme and the selection guideline.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1256-1263
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• 2004

Output feedback passivation problem is studied when the given system is not minimum-phase or does not have relative degree one. Using a parallel connection with an additional dynamics, the authors provide a dynamic output feedback control law which renders the composite system passive. Sufficient conditions are presented under which the composite system is output feedback passive. As an application of the dynamic passivation scheme, a point-to-point control law for a flexible joint robot is presented when only the position measurements are available. This provides an alternative way of replacing the role of the velocity measurements for the proportional-derivative (PD) feedback law. The performance of the proposed control law is illustrated in the simulation studies of a manipulator with three revolute elastic joints.

• Structural Engineering and Mechanics
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• v.12 no.6
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• pp.633-656
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• 2001

In this paper, modal control with direct output feedback is formulated in a systematic manner for easy implementation. Its application to the seismic protection of structural systems is verified by a shaking table test, which involves a full-scale building model and an active bracing system as the control device. Two modal control cases, namely, one full-state feedback and one direct output feedback control were tested and compared. The experimental result shows that in mitigating the seismic response of building structures, modal control with direct output feedback can be as effective and efficient as that with full-state feedback control. For practical concerns, the control performance of the proposed method in the presence of sensor noise and stiffness modeling error was also investigated. The numerical result shows that although the control force may be increased, the maximum floor displacements of the controlled structure are very insensitive to sensor noise and modeling error.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1604-1607
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• 2004

In this paper, we consider a problem of asymptotic output regulation of a class of uncertain nonlinear systems by output feedback. The system under consideration is in the Parametric-Pure-Feedback Form, which does not satisfy the existing conditions such as the triangularity condition or the Lipschitz condition. We propose a linear output feedback controller with a scaling factor, which asymptotically regulates the output of the considered system.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.4
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• pp.593-603
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• 2016

This paper presents the development of linear quadratic regulation and output tracking algorithms using output feedback when both the measurement and performance output equations contain direct feedthrough terms. Although all physical systems can be modeled without direct feedthrough, there are still many situations where system models with direct feedthrough are important. For this situation, we modify previous work on the same topic for systems without direct feedthrough. It is shown that for the regulation problem, the optimal output feedback gain for a direct feedthrough case can be directly obtained, via a transformation, from the approach used for systems without direct feedthrough. However, for the tracking problem, a new set of coupled matrix equations for determining the optimal output feedback gain is derived from the necessary conditions for minimizing the cost function. The effectiveness of the developed algorithms is demonstrated using numerical examples.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.526-528
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• 2006

An adaptive output-feedback neural control problem of SISO strict-feedback nonlinear system is considered in this paper. The main contribution of the proposed method is that it is shown that the output-feedback control of the strict-feedback system can be viewed as that of the system in the normal form. As a result, proposed output-feedback control algorithm is much simpler than the previous backstepping-based controllers. Depending heavily on the universal approximation property of the neural network (NN) only one NN is employed to approximate lumped uncertain nonlinearity in the controlled system.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.299-303
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• 2011

In this paper, we propose an output feedback controller for a chain of integrators system compensating measurement noise of feedback sensor. Measurement noise makes feedback signals distorted, and results in performance degradation or even system failure. Therefore, we need to design a robust controller to accommodate the possible measurement noise in the feedback information. Our controller is equipped with a gain-scaling factor to reject or minimize the effect of measurement noise in output feedback information. We give a theoretical analysis of the controlled system and illustrate the improved control performance via an example.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.386-391
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• 2003

This paper focuses on robust $H_{\infty}$ control for bilinear systems with time-varying parameter uncertainties and exogenous disturbance via output feedback. $H_{\infty}$ control is achieved via separation into a $H_{\infty}$ state feedback control problem and a $H_{\infty}$ state estimation problem. The suitable robust stabilizing output feedback control law can be constructed in term of approximated solution to x-dependent Riccati equation using successive approximation technique. Also, the $H_{\infty}$ filter gain can be constructed in term of solution to algebraic Riccati equation. The output feedback control robustly stabilizes the plant and guarantees a robust $H_{\infty}$ performance for the closed-loop systems in the face of parameter uncertainties and exogenous disturbance.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.560-564
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• 2015

This paper presents a design method of a static output feedback controller for continuous T-S fuzzy systems via parallel distributed compensation (PDC). The existence condition of a set of static output feedback gains is represented in terms of linear matrix inequalities (LMIs). The sufficient condition presented here does not need any transformation matrices and equality constraints and is less conservative than the previous results seen in [20].

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1298-1301
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• 2007

The problem of designing dynamic output feedback sliding mode controllers for uncertain multivariable linear systems is considered. Using linear matrix inequalities(LMIs), a feasibility condition for the design problem is derived. Explicit fomulas of the gain matrices of a full order output feedback sliding mode controller in terms of the solution matrices of the LMI condition is given. A simple LMI-based algorithm for designing output feedback sliding mode controllers is also given. Finally, numerical design examples are given to show the effectiveness of the proposed method.