• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1892-1896
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• 2005

In this paper, an effective method for selecting significant input variables in building ANFIS (Adaptive Neuro-Fuzzy Inference System) for nonlinear system modeling is proposed. Dominant inputs in a nonlinear system identification process are extracted by evaluating the performance index and they are applied to ANFIS. The availability of our proposed model is verified with the Box and Jenkins gas furnace data. The comparisons with other methods are also given in this paper to show our proposed method is superior to other models.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.842-846
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• 1996

Leaf springs are widely used as a major suspension component in many commercial vehicles, such as buses, trucks, etc. They have a complex dynamic behavior due to the geometric nonlinear and the contact mechanism between the leaves. The interface conditions between the leaves play a significant role in the global behavior of the comfort and ride of the vehicle system. The paper concentrates on modeling leaf springs and contact frictions between the leaves using a nonlinear finite element approach. A nonlinear load-displacement hysteresis curve for the leaf spring is simulated and its results are compared with test results.

• 전기학회논문지
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• 제59권5호
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• pp.1001-1004
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• 2010

Acoustic feedback and background noise variation can degrade the performance of an active noise control (ANC) system. In this paper, nonlinear ANC using a non-parametric VSS-NLMS (or NPVSS-NLMS) algorithm and online feedback path modeling is proposed, whereby the conventional linear ANC with online acoustic feedback-path modeling is further extended to nonlinear Volterra ANC with a linear acoustic feedback path. In particular, the step-size of the NPVSS-NLMS algorithm is controlled to reduce the effect of background noise variation in the ANC system. Simulation results demonstrate that the proposed approach yields better nonlinear ANC performance compared with the conventional nonlinear ANC method.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권3호
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• pp.142-147
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• 2003

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 uncertainty. 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 presence of input coefficient uncertainty.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.959-961
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• 1996

In this paper, we study the modeling and control of Electro-Magnetic Suspension System with 2 Degree Of Freedom. While the previous researchers considered the control of single rail EMS Systems, we consider the control of two rail EMS Systems. We first derive a simple model to represent the dynamics of EMS System with 2 D.O.F., using the Lagrange's method. The nonlinear equations of motion that we derive are shown to be linearizable by coordinate change and nonlinear static state feedback. The nonlinear static state feedback controller is constructed explicitly.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.975-976
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• 2008

Reliable channel modeling becomes an important measure in performance evaluation on various data detection algorithms. For this reason, correct and accurate modeling is required. This paper presents a nonlinear modeling of Super-RENS (Super-Resolution Near Field Structure) read-out signal using the second-order Volterra model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2551-2554
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• 2003

In this paper, we describe the nonlinear character for a friction control. The nonlinear character of friction control is inherent in mechanical system, which has gained more and more interest. The modeling and compensation of nonlinear friction are difficult tasks for precise motion control. This paper is performance evaluation of nonlinearities and mechanical compliance exists together with friction control system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.346-351
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• 1987

In this study, digital simulation with nonlinear modeling is carried out to analyse the performance of a hydraulic servomotor system developed for the position control of a large inertia. Nonlinear element, such as nonlinear pressure flow relationships of servovalve, valve spool limits, nonlinear friction, and backlash and resilience of gear system are included in the simulation along with the dynamic characteristics of variable delivery pump compensation mechanism. Simulation results are compared with experimental results for both step and sinusoidal inputs. Independent of input magnitude, both results are in good agreement with minor differences in detail.

• 전기학회논문지P
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• 제57권2호
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• pp.96-101
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• 2008

The field of load modeling has attracted the attention since it plays an important role for improving the accuracy of stability analysis and power flow estimation. Also, load modeling is an essential factor in the simulation and evaluation of power system performance. However, conventional load modeling techniques have some limitations with respect to accuracy for nonlinear and composite loads. Thus, precision load modeling technique and reasonable application method is needed for more accurate power system analysis. In this paper, we develop an intelligent load modeling method based. on neural network and application techniques for power system. The proposed method makes it possible to effectively estimate the load model for nonlinear models as well as linear models. Reasonable application method is also proposed for stability analysis. To demonstrate the validity of the proposed method, various experiments are performed and their results are presented.

• 한국정밀공학회지
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• 제33권3호
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• pp.183-190
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• 2016

In this study, we conduct linear and nonlinear modeling of the DC motor driving system of a wheeled mobile robot, which is a nonlinear system involving dead zone, friction, and saturation. The DC motor driving system consists of a DC motor, a wheel, and gears. A linear DC motor driving system is modeled using a steady-state response and parameter measurements. A nonlinear DC motor driving model is identified with the use of the Hammerstein-Wiener method. By using these models, PID controllers for the DC motor system are then established. Each PID controller is applied as a low-level controller in order to achieve posture stabilization control for the real mobile robot. We also compare the performance of the proposed PID controllers in posture stabilization experiments by using several different final robot postures.