• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.448-451
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• 2000

Fuzzy control has been researched for application of industrial processes which have no accurate mathematical model and could not controlled by conventional methods because of a lack of quantitative input-output data. Intelligent control approach based on fuzzy logic could directly reflex human thinking and natural language to controller comparing with conventional methods. In this paper, the tested system is constructed for sending a ball to the goal position using wind from two DC motors in the path. This system contains non-linearity and uncertainty because of the characteristic of aerodynamics inside the path. The system used in this experiment could be hardly modeled by mathematic methods and could not be easily controlled by linear control manners. The controller, in this paper could control the system containing non-linearity and uncertainty because it is designed based on the input-output data and experimental knowledge obtained by trials.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.432-437
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• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently fuzzy controllers have become quite popular for robust control due to its capability of dealing with unstructured uncertainty. Thus in this paper we design an adaptive fuzzy controller using an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Simulation results show that satisfactory performance is achieved by the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.70.3-70
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• 2002

This paper presents a procedure of implementing a robust controller for a paper-making plant in DCSs. A paper-making process generally has triple problems to automatically tune its output qualities . Long transport delays which are not able to be simply linearized. The transfer matrix of the process is not square. And every plant model has some uncertainty in low and middle frequency region. To tackle these problems, a multi-input / multi-output (MIMO) plant model having some uncertainty was derived by considering some physical and mechanical principles of the process. Then a MIMO robust-controller is designed and implemented in a real DCS as function block type. Some special co...

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.233-236
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• 2002

We consider a single-input-single-output nonlinear system which can be represented in a normal form. The nonlinear system has a modeling uncertainties including the input coefficient uncertainties. A high-gain observer is used to estimate the states variables to reject a modeling uncertainty. A globally bounded output feedback integral sliding mode control is proposed to stabilize the closed loop system. The proposed integral sliding mode control can asymptotically stabilize the closed loop system in the it presence of input coefficient uncertainty.

• Journal of Electrical Engineering and information Science
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• v.2 no.4
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• pp.28-36
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• 1997

In this paper, robust stability analysis for the fuzzy feedback linearization regulator is presented. Well-known Takagi-Sugeno fuzzy model is used as the MISO nonlinear plant model. Uncertainty and disturbance are assumed to be included in the model structure with known bounds. For these structured uncertainty and disturbances, robust stability of the close system is analyzed in both input-output sense and Lyapunov sense. The robust stability conditions are proposed by using multivariable circle criterion and the relationship between input-output stability and Lyapunov stability. The proposed stability analysis is illustrated by a simple example.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.418-421
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• 1997

A control synthesis scheme is presented for nonlinear single-input-single-output (SISO) systems with parametric uncertainty which have completely unstable zero dynamics. The approach involves the derivation of an input-output linearizing control law which achieves internal stability for a nonlinear minimum phase approximation to the original system using Fliess normal form. A vector of unknown constant parameters is also considered. A Lyapunov-based additional control law is shown to stabilize the full system.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.122-126
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• 2005

A technique for alignment to true north is presented based on synchronized measurements of vision image by a camera and output voltage of wind direction sensor. The true wind direction is evaluated by means of image processing techniques with least square sense, and then evaluated true value is compared with measured output voltage of the sensor. The uncertainty analysis about the component error for the proposed method in practical situation is performed. The proposed technique is applied to real meteorological tower (wind measuring tower) at the Daekwanryung test site. In addition, some uncertainty analysis of this method is presented.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.2-2
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• 2000

This paper presents an adaptive control against uncertainties in tail-controlled STT (skid-to-Turn) missiles. First, we derive an analytic uncertainty model from a parametricaffine missile model developed by the authors. Based on this analytic model, an adaptive feedbacklinearizing control law accompanied by a sliding model control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme is demonstrated by simulation.

• Journal of IKEEE
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• v.22 no.1
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• pp.110-120
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• 2018

In this paper, we apply the input-output linearization technique to tracking the follow-up trajectory r(t) in the ball-beam system. There exist system disturbance and various uncertainties, the conventional input-output linearization based control yields some noticeable errors in tracking performance. As a result, a new robust control technique for the uncertainty of the system was proposed and its improved performance verified through simulation and experimental results. So, more realistic system model is obtained with unmatched uncertainties and disturbance. Then, in order to improve the control performance, a new optimal bang-bang control input is additionally added.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.273-282
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• 1996

This work is conceded with the estimation of output derivatives and their use for the design of robust controller for linear systems with system uncertainties due to modeling errors and disturbances. It is assumed that a nominal transfer function model and quantitative bounds for system uncertainties and known. The developed control schemes are shown to achieve regulation of the system output and ensures boundedness of the system states without imposing any structural conditions on system uncertainties and disturbances. Output derivative estimation is first conducted through restructuring of the plant in a specific parameterization. They are utilized for constructing robust nonlinear high-gain feedback controller of a SMC(Sliding Mode Control)type. The performances of the developed controller are evaluated and shown to be effective and useful through simulation study.