• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.3
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• pp.48-52
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• 2011

This paper presents the observer based output feedback control design for linear systems which have both input and output time delay. Sufficient conditions for existence of stabilizing output feedback controller are characterized by linear matrix inequalities. Since the condition of the proposed design depends on the value of time delay, it is less conservative than existing delay-independent approaches. Finally, an illustrative example is given in order to show the effectiveness of our design method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.977-983
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• 2003

An output feedback stabilizing controller far non-minimum phase nonlinear systems is presented. We first perform the standard input-output linearization of the system and then transform the zero dynamics into a special normal form in which the antistable part is not affected by the stable part and the antistable part is given in approximately linear form. Under the assumption that the nonlinear system satisfies the observability rank condition, we can design an observer f3r the extended system that is made of the augmentation of a chain of integrators. The proposed output feedback stabilizing controller can then be designed by combining the observer and the state feedback controller.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.96-100
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• 2003

In this paper, a DLC method is proposed for linear feedback systems to improve the tracking performance when the task of the system is repetitive. DLC can generate the desired control input directly from the previously learned control inputs corresponding to other output trajectories. It is assumed that all the desired output functions considered in this paper have some relations called proportionality and it is shown by mathematical analysis that DLC can be utilized to generate additional control efforts for the perfect tracking. To show the validity and tracking performance of the proposed method, some simulations are performed for the tracking control of a linear system with a PI controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.76-80
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• 2005

In this paper, a Direct Learning Control (DLC) method is proposed for linear feedback systems to improve the tracking performance when the task of the control system is repetitive. DLC can generate the desired control input directly from the previously learned control inputs corresponding to other output trajectories. It is assumed that all the desired output functions given to the system have some relations called proportionality and it is shown by mathematical analysis that DLC can be utilized to genera additional control efforts for the perfect tracking. To show the validity and tracking performance of the proposed method, some simulations are performed for the tracking control of a linear system with a PI controller.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.48.1-48
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• 2001

In this paper, we present a global adaptive output feedback control scheme for a class of uncertain nonlinear systems to which adaptive observer backstepping method may not be applicable directly. The allowed output feedback structure includes quadratic and multiplicative dependency of unmeasured states. Our novel design technique employs a change of coordinates and adaptive backstepping. With these proposed tools, we can remove linear and quadratic dependence on the unmeasured states in the state equation. Also, the multiplication of the two unmeasured states can be eliminated ...

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.389-395
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• 2007

In this paper, we consider the robust non-fragile $H_{\infty}$ output feedback controller design method for uncertain descriptor systems with feedback and observer gain variations. The existence condition of observer-based robust and non-fragile $H_{\infty}$ output feedback controller and the controller design method are Presented on the basis of linear matrix inequality approach. The proposed robust non-fragile $H_{\infty}$ output feedback controller guarantees asymptotic stability, non-fragility, $H_{\infty}$ norm bound within a prescribed level in spite of disturbance, parameter uncertainty, and feedback/observer gain variations.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.529-534
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• 2005

In this paper, a new type of output feedback control, called a $H_2/H_{\infty}$ fnite memory control (FMC), is proposed for deterministic state space systems. Constraints such as linearity, unbiasedness property, and finite memory structure with respect to an input and an output are required in advance to design $H_2/H_{\infty}$ FMC in addition to the performance criteria in both $H_2$ and $H_{\infty}$ sense. It is shown that $H_2$, $H_{\infty}$, and mixed $H_2/H_{\infty}$ FMC design problems can be converted into convex programming problems written in terms of linear matrix inequalities (LMIs) with some linear equality constraints. Through simulation study, it is illustrated that the proposed $H_2/H_{\infty}$ FMC is more robust against uncertainties and faster in convergence than the existing $H_2/H_{\infty}$ output feedback control schemes.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.587-591
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• 2013

This paper addresses the robust fault tolerant controller design problems of static output systems with disturbance. The fault is expressed by the abrupt chattering of system parameters. The design conditions are derived in terms of linear matrix inequalities and linear matrix equalities. An illustrative example is provided to verify performances of the proposed controller.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.1
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• pp.20-28
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• 2014

This paper presents static output feedback LQ and $H_{\infty}$ controllers for rollover prevention. Linear quadratic static output feedback controllers have been proposed for rollover prevention in such a way to minimize the lateral acceleration and the roll angle. Rollover prevention capability can be enhanced if $H_{\infty}$ controller is designed. To avoid full-state measurement for feedback requirement or sensitiveness of an observer to nonlinear model error, static output feedback is adopted. To design static output feedback controllers, Kosut's method is adopted because it is simple to calculate. Differential braking and active anti-roll bar are adopted as actuators that generate yaw and roll moments, respectively. The proposed method is shown to be effective in preventing rollover through the simulations on nonlinear multi-body dynamic simulation software, CarSim.