• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.266-278
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• 1987

This paper addresses the issues in setting performance criteria for safety regulation of nuclear power plants. Since setting criteria at the low level is a much more difficult task than it is at the top level, the low-level performance criteria should be derived consistently from the more easily determinable top-level performance criteria. The paper also proposes several approaches to characterizing uncertainties in performance criteria, by extending the reliability allocation methodology that is based on the mean-to-mean mapping to a stochastic multi-objective optimization problem where the state variables are uncertain.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.173-178
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• 1993

In this paper, we present an algorithmic technique for determining a feedback compensator which will stabilize the interval dynamic system, specifically, the robust regulator design for interval plants. The approach taken here is to allow the system parameters to live within prescribed intervals then design a dynamic feedback compensator which guarantees closed-loop system stable. The main contribution of this paper is the idea of introducing a "simplified Kharitonov's result" for low order polynomials to search for suitable compensator parameters in the compensator parameter space to make the uncertain syste robust. We also design the robust regulator which will D-stabilize (have the closed-loop poles in the left sector only) the dynamic interval system while having good performance. The nuerical examples are given to show the substantially improved robustness which results from our approach. approach.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.498-503
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• 1993

In this paper, a robust and reliable H$_{\infty}$ control problem is considered for linear uncertain systems with time-varying norm-bounded uncertainty in the state matrix, which performs well despite of actuator outages. Using linear static state feedback and the quadratic stabilization with H$_{\infty}$-norm bound, a robust and reliable H$_{\infty}$ controller is obtained that stabilizes the plant and guarantees an H$_{\infty}$-norm bound constraint on disturbance attenuation for all admissible uncertainties and normal state as well as faulty state of actuators. It provides a sufficient condition for robust and reliable stabilization with H$_{\infty}$-norm bound. Reliability is guaranteed provided actuator outages only occur within a prespecified subset of actuators.tors.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.546-551
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• 1993

A new robust sliding mode controller is formulated for the tip position control of a single-link flexible manipulator with parameter variations. After establishing the plant model characterized by a noncollocated uncertain control system, a sliding surface which guarantees stable sliding mode motion is synthesized in an optimal manner. The surface is then modified to adapt arbitrarily given initial conditions. A discontinuous control law associated with the modified surface is designed by restricting that velocity state variables are not available from direct sensor measurements. Using the proposed control law favorable system responses are accomplished through shortening the reaching phase of state trajectory without increasing maximum control torque as well as undesirable chattering. Furthermore, a low sensitiveness to uncertainties is obtained from inherent salient properties of the proposed control system. Computer simulations are undertaken in order to demonstrate these superior control performance characteristics to be accrued from the proposed methodology.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.181-184
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• 1997

This paper propose the systematic procedure of the fuzzy model based controller for the continuous nonlinear system. Fuzzy controller have been successfully applied to many uncertain and complex industrial plants. The design of the fuzzy controller mainly depends on the knowledge from the expert who are familiar with the plant by trial and error. Therefore we need more systematic approach to the design of the fuzzy controller. In this paper, we design fuzzy model based controller applied to the nonlinear system. Unlike the design procedures reported in[8] and[9], we use the nonlinear process directly in designing the controller. This controller has been successfully applied to an inverted pendulum.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.557-562
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• 2004

This paper deals with a robust mixed ${H_2}/{H_{\infty}}$ filter design problem for a nonlinear dynamic system modeled as a T-S fuzzy system. Integral quadratic constraints are used to describe various kinds of uncertainties of the plant. A sufficient condition for solvability is given in terms of linear matrix inequality problem which can be efficiently solved using a convex optimization technique. In order to demonstrate the Proposed method, a numerical design example is provided.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.5
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• pp.94-98
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• 2012

Butterfly valves are usually used by the plumbing systems in plant engineering field. Valves are used for controlling the flow rate and pressure of fluid. In order to control the flow rate using butterfly valve, the position control of valve disc should be designed. However, since there are lots of uncertain disturbance in plumbing system, the robust control system should be considered. Therefore, the sliding mode control system using neural network algorithm is proposed in this paper. The proposed control system provides the estimating method using neural network for the unmeasurable disturbance in the plumbing system. The performance of the proposed control system is evaluated through computer simulations.

• Journal of the Korean Society for Precision Engineering
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• v.6 no.2
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• pp.88-97
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• 1989

In general turret servo system is subject to influnces by disturbances and uncertain modeling errors, which result from large dynamic characteristics and high-spedd operation. In this paper the influences of such disturbances and modeling errors are analyzed quali- tatively for the linerar approximation model of turret servo system, and then LQG/LTR control theory is applied to linear approximation model in order to design a controller which satisfies robustness/stability for the modeling errors. Finally the performance and robustness of designed controller for the given plant are verified through the simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.88-93
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• 1995

This paper presents a study using neural networks in the design of the tracking controller of robotic systems. Our strategy is to put to use the available knowledge about the robot manipulator, such as estimation models, in the contoller design via the computed torque method, and then to add the neural network to control the remaining uncertainty. The neural network used here learns to provide the inverse dynamics of the plant uncertainty, and acts as an inverse controller. In the simulation study, we verify that the proposed neural network controller is robust not only to structured uncertainties, but also to unstructured uncertainties such as friction models.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1188-1193
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• 2011

A nonlinear version of disturbance observer is presented. The system under consideration is an uncertain single input single output nonlinear system and the nominal plant is also a nonlinear system. Compared to the previous implementation given in [8], the proposed scheme does not require an auxiliary variable anymore, thus it has a simpler and more intuitive structure. A robust stability condition for the overall closed-loop system is also provided.