• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.177-180
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• 1996

The purpose of this paper is to design a robust adaptive control algorithm for a class of systems having continuous relay nonlinearity. This continuous relay nonlinearity can be defined as an analytic nonlinear function having unknown parameters and bounded unmodeling part. By this mathematical modeling, the whole system can be considered as a nonlinear system having unknown parameters and bounded perturbation. The control algorithm of this paper, RALC, can be constructed by robust adaptive law, feedback linearization, and indirect robust adaptive control. By this RALC, we can obtain that the output of given system can follow that of a stable reference linear model made by designer and the boundedness of all signals in closed-loop system can be maintained. Therefore, we can confirm a robust adaptive control for a class of systems having continuous relay nonlinearity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.9
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• pp.1264-1269
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• 2013

In this paper, we study a disturbance observer (DOB) based controller for an EMS(Electro-Magnetic Suspension) system in presence of mass uncertainty and input disturbance. The DOB based controller is employed in order to compensate the modeling uncertainty and attenuate disturbance signals. For the design of DOB based controller, the Jacobain linearization of nonlinear system model equation is used. Computer simulation is carried out for nonlinear model in order to compare the performance of the proposed DOB controller with that of the conventional PID controller. The simulation results show that the substantial improvement in the performance can be achieved by the proposed DOB controller.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.226-228
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• 2006

This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems are used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system, we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem, and convergence and robustness properties are demonstrated. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• Earthquakes and Structures
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• v.3 no.6
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• pp.853-867
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• 2012

In this paper, a new type of passive energy dissipating system similar to added damping and stiffness (ADAS) and triangular added damping and stiffness (TADAS) is proposed and implemented in the analytical model of a building with hybrid structural system in the structure's base which we call it; Telescopic column. The behavior and performance of a high rise R.C. structure equipped with this system is investigated and compared with conventional base isolation systems such as rubber isolator bearings and friction pendulum bearings. For this purpose a series of ground acceleration records of the San Fernando, Long Beach and Imperial Valley earthquakes are used as the disturbing ground motions in a series of numerical simulations. The nonlinear numerical modeling which includes both material and geometric nonlinearities were carried out by using SAP2000 program. Results show suitable behavior of structures equipped with telescopic columns in controlling the upper stories drifts and accelerations.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.720-723
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• 1997

The characteristics of ball and beam system using fuzzy inference technique can be described by fuzzy modeling. Therefore, this paper introduces a technique for fuzzy structure identification of nonlinear Input-output relation- ship using an adaptive fuzzy inference system. And the simulation result using adaptive fuzzy inference technique shows its effectiveness for fuzzy structure identification of nonlinear system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.216-220
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• 2007

Camera calibration in machine vision is the process of determining the intrinsic camera parameters and the three-dimensional (3D) position and orientation of the camera frame relative to a certain world coordinate system. On the other hand, Takagi-Sugeno-Kang (TSK) fuzzy system is a very popular fuzzy system and approximates any nonlinear function to arbitrary accuracy with only a small number of fuzzy rules. It demonstrates not only nonlinear behavior but also transparent structure. In this paper, we present a novel and simple technique for camera calibration for machine vision using TSK fuzzy model. The proposed method divides the world into some regions according to camera view and uses the clustered 3D geometric knowledge. TSK fuzzy system is employed to estimate the camera parameters by combining partial information into complete 3D information. The experiments are performed to verify the proposed camera calibration.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.247-248
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• 2012

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.2
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• pp.108-113
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• 2016

The real-world problems usually show nonlinear and multi-variate characteristics, so it is difficult to establish concrete mathematical models for them. Thus, it is common to practice data-driven modeling techniques in these cases. Among them, most widely adopted techniques are regression model and intelligent model such as neural networks. Regression model has drawback showing lower performance when much non-linearity exists between input and output data. Intelligent model has been shown its superiority to the linear model due to ability capable of effectively estimate desired output in cases of both linear and nonlinear problem. This paper proposes modeling method of daily photovoltaic power systems using ELM(Extreme Learning Machine) based modular networks. The proposed method uses sub-model by fuzzy clustering rather than using a single model. Each sub-model is implemented by ELM. To show the effectiveness of the proposed method, we performed various experiments by dataset acquired during 2014 in real-plant.

• Journal of IKEEE
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• v.26 no.4
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• pp.577-583
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• 2022

Verilog-HDL-based modeling can be performed to confirm the fast operation characteristics after setting the design parameters of each block considering the stability of the system by performing linear phase-domain modeling on the phase-locked loop. This paper proposed Verilog-HDL modeling including DCO noise and DTC nonlinear characteristic. After completing the modeling, the time-domain transient simulation can be performed to check the feasibility and the functionality of the proposed PLL system, then the phase noise result from the system design based on the functional model can be verified comparing with the ideal phase noise graph. As a result of the comparison of simulation time (6 us), the Verilog-HDL-based modeling method (1.43 second) showed 484 times faster than the analog transistor level design (692 second) implemented by TSMC 0.18-㎛.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.