• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.92-94
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• 2007

This paper considers an optimal control problem for a remote control to an electrical drive system with a DC motor. Since it is a linear control system with time-delay subject to unknown but bounded disturbance, we construct a worst-case feedback control policy. This policy can guarantee that, for all admissible uncertain disturbances, the real system state should be in a prescribed neighborhood of a desired value, and the cost functional takes the best guarantee value. The worst-case feedback control policy is allowed to be corrected at one correction point between the initial to the final time, which is equivalent to solving a 1-level min-max problem. Since the min-max problem at the stage does not yield a simple analytical solution, we consider an approximate control policy, which is equivalent and can be solved explicitly m the numerical experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.9
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• pp.929-938
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• 2009

This paper presents a novel control methodology for communication network based nonlinear systems with time delay nature. We construct a nominal nonlinear control law for representing a linear model and a reset control system which is aimed for corrective control strategy to compensate system error due to uncertain time delay through wireless communication network. Next, online neural control approach is proposed for overcoming nonstationary statistical nature in the network topology. Additionally, DBN (Dynamic Bayesian Network) technique is accomplished for modeling of its dynamics in terms of casuality, which is then utilized for estimating prediction of system output. We evaluate superiority and reliability of the proposed control approach through numerical simulation example in which a nonlinear inverted pendulum model is employed as a networked control system.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1134-1136
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• 1996

A necessary and suficient conditions is proposed for feedback linearizable SISO systems with unknown constant parameters. It is shown that the systems which satisfy the proposed conditions can be transformed into a controllable linear system with unknown parameter and it can be stabilized using the nonlinear feedback linearizing controller. We also present the analysis and implementation of a nonlinear feedback linearizing control for an Electro-Magnetic Suspension (EMS) system. We show that an EMS system is nonlinear feedback linearizable and satisfies the proposed conditions, and hence that the proposed nonlinear feedback controller for an EMS system is robust against mass parameter perturbation and force disturbance.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1949-1951
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• 2001

This paper deals with the control of a nonlinear experimental helicopter system by using the fuzzy-model-based control approach. The fuzzy model of the experimental helicopter system is constructed from the original nonlinear dynamic equations in the form of an affine Takagi-Sugeno (TS) fuzzy system. In order to design a feasible switching-type fuzzy-model-based controller, the TS fuzzy system is converted to a set of uncertain linear systems, which is used as a basic framework to synthesize the fuzzy-model-based controller.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.3
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• pp.623-630
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• 2001

The conventional control techniques based a mathematical model are not well suited for dealing with ill-defined and uncertain system like a linear quadratic control. Recently, fuzzy control has been successfully applied to a wide variety of practical problems such as robot, water purification, automatic train operation system etc. In this paper, a design technique of robust Fuzzy-LQ controller for each subsystem is designed. Secondly , all the subsystem controllers are combined by fuzzy weighted averaging method. Finally the effectiveness of the proposed controller is verified through a series of computer simulations for an inverted pole system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.188-188
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• 2000

The most important problem in target tracking can be said to be modeling the tracking system correctly. Although the simple linear dynamic equation for this model has used until now, the satisfactory performance could not be obtained owing to uncertainties of the real systems in the case of designing the filters baged on the dynamic equations. In this paper, we propose the extended robust Kalman filter (ERKF) which can be applied to the real target tracking system with the parameter uncertainties. A nonlinear dynamic equation with parameter uncertainties is used to express the uncertain system model mathematically, and a measurement equation is represented by a nonlinear equation to show data from the radar in a Cartesian coordinate frame. To solve the robust nonlinear filtering problem, we derive the extended robust Kalman filter equation using the Krein space approach and sum quadratic constraint. We show the proposed filter has better performance than the existing extended Kalman filter (EKF) via 3-dimensional target tracking example.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.63-64
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• 2007

In this paper, an adaptive passivity based excitation and governor control scheme is proposed to enhance the transient stability of a single machine infinite bus power system with parametric uncertainties. We employ a state model where the frequency, the difference between active and mechanical power, and the difference between the squared terminal voltage and its reference are regarded as state variables. Using this state model, the proposed controller is obtained in two steps; firstly, a simple direct adaptive passivation controller is designed for the power system with parametric uncertainties; then a linear PI controller is applied to guarantee the stability of the closed loop system.

• Journal of Ocean Engineering and Technology
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• v.17 no.4
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• pp.59-65
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• 2003

In order to achieve the desired lightweight and robust design of a structure, it is preferable to design a structure and its control system, simultaneously, which is termed the combined optimal design. A constant-cross-sectional area cantilever beam was chosen as the optimum design method, An initial load and a time-varying disturbance were applied at the free end of the beam. Sliding mode control was selected, due to its insensitivity to the disturbance, compared with other modes. It is known that the sliding mode control is robust to the disturbance and is uncertain, only if a matching condition is met, after giving a switching hyper plane. In this study, the optimum method was used for the design of the switching hyper plane, and the objective function of the optimum switching hyper plane was assumed to be the objective of the control system. The total weight of the structure was treated as a constraint, and the cross sectional areas of the beam were considered as design variables, the result being a nonlinear programming problem. To solve it, the sequential linear programming method was applied. As a result of the optimum design, the effect of attenuating vibrations has been substantially improved. Moreover, the lightweight design of the structure became possible as a result of the relationship of the weight of the structure to the control objective function.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.32-41
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• 2008

In this paper, we describe the synthesis of robust and non-fragile $H^{\infty}$ state feedback controllers for linear systems with affine parameter uncertain tracking servo system of blu-ray disc drive, as well as static state feedback controller with polytopic uncertainty Similarity any other control system, the objective of the track-following system design for optical disc drives is to construct the system with better performance and robustness against modeling uncertainties and various disturbances. Also, the obtained condition can be rewritten as parameterized linear matrix inequalities(PLMIs), that is, LMIs whose coefficients are functions of a parameter confined to a compact set. 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 resulted polytopic region.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.3
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• pp.17-24
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• 2004

We present a P-type iterative learning control(ILC) scheme for uncertain robotic systems that perform the same tasks repetitively. The proposed ILC scheme comprises a linear feedback controller consisting of position error, and a feedforward and feedback teaming controller updated by current velocity error. As the learning iteration proceeds, the joint position and velocity mrs converge uniformly to zero. By adopting the learning gain dependent on the iteration number, we present joint position and velocity error bounds which converge at the arbitrarily tuned rate, and the joint position and velocity errors converge to zero in the iteration domain within the adopted error bounds. In contrast to other existing P-type ILC schemes, the proposed ILC scheme enables analysis and tuning of the convergence rate in the iteration domain by designing properly the learning gain.