• 한국자동차공학회논문집
• /
• 제24권6호
• /
• pp.730-736
• /
• 2016

Recent research suggests the various applications of Model Predictive Control on vehicle systems. In numerous cases, nonlinear tire models such as the Magic Formula, which are highly complex and are more detailed than necessary, are used. This paper presents a nonlinear tire model that excludes the region of negative slope but expresses the nonlinear properties of tire well enough for tracking the lane of a racing course. The proposed inverse tire model can also be used to calculate the slip angle from the tire force. Thus, the model can be utilized to design the Model Predictive Controller.

• 한국해안·해양공학회논문집
• /
• 제20권1호
• /
• pp.121-127
• /
• 2008

비선형의 정도에 따른 Boussinesq 모형의 특성을 비교하기 위해 약비선형 모형인 MIKE21 BW 모듈과 완전비선형 모형인 FUNWAVE 모형을 이용하여 수치실험을 수행하였다. 진폭별 조파실험, 심해 파형경사별 천수실험 그리고 사주 지형상의 파랑 전파실험을 수행하였고, 이상의 실험을 통해 비선형성이 부각되는 천해역에서 비선형 모형의 중요성을 확인하였다. 특히 완전 비선형 모형이 약비선형 모형에 비해 비대칭 파형의 재현성이 우수하고, 천수현상에 따른 파고의 증가가 상대적으로 크게 나타나는 모형 간 특성을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.90-95
• /
• 2003

In this paper, an Adaptive Nonlinear Constrained Model Predictive Control (ANCMPC) is presented for a pH control in a fed-batch bio-reactor. The pH model is represented with Hammerstein Model. The static nonlinear part of Hammerstein model is described with the static pH model, and the dynamic linear part of the Hammerstein model is described with the CARIMA model. The parameters of the CARIMA model is estimated on-line with the input and output measurements of the system using a recursive least squares type of identi�cation algorithm. The e�ectiveness of the proposed controller is shown through simulations.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2007년도 제38회 하계학술대회
• /
• pp.1728-1729
• /
• 2007

This paper presents an adaptive neural dynamic surface control (DSC) approach with $H_{\infty}$ tracking performance for a full dynamics of a nonlinear flight system. It is assumed in this paper that model uncertainties such as structured and unstrutured uncertainties and external disturbances influence the nonlinear aircraft model. In our control system, self recurrent wavelet neural networks (SRWNNs) are used to compensate model uncertainties of the nonlinear flight system, and an adaptive DSC technique is extended for disturbance attenuation of the nonlinear flight system. From Lyapunov stability theorem, it is shown that $H_{\infty}$ performance from external disturbances can be obtained. Finally, we perform the simulation for the nonlinear six-degree-of-freedom F-16 aircraft model to confirm the effectiveness of the proposed control system.

• Geomechanics and Engineering
• /
• 제12권2호
• /
• pp.239-255
• /
• 2017

Various centrifuge model tests on the pile foundations were performed to investigate fundamental characteristics of a pile-soil-foundation system recently, but it is hard to find numerical analysis results of a pile foundation system considering the nonlinear behavior of soil layers due to the dynamic excitations. Numerical analyses for a pile-soil system were carried out to verify the experimental results of centrifuge model tests. Centrifuge model tests were performed at the laboratory applying 1.5 Hz sinusoidal base input motions, and nonlinear numerical analyses were performed utilizing a finite element program of P3DASS in the frequency domain and applying the same input motions with the intensities of 0.05 g~0.38 g. Nonlinear soil properties of soil elements were defined by Ramberg-Osgood soil model for the nonlinear dynamic analyses. Nonlinear numerical analyses with the P3DASS program were helpful to predict the trend of experimental responses of a centrifuge model efficiently, even though there were some difficulties in processing analytical results and to find out unintended deficits in measured experimental data. Also nonlinear soil properties of elements in the system can be estimated adequately using an analytical program to compare them with experimental results.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
• /
• pp.303-306
• /
• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKF uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• Journal of Electrical Engineering and Technology
• /
• 제11권2호
• /
• pp.265-273
• /
• 2016

A water wall system is one of the most important components of a boiler in a thermal power plant, and it is a nonlinear Multi-Input and Multi-Output (MIMO) system, with 6 inputs and 3 outputs. Three models are developed and comp for the controller design, including a linear model, a multilayer feed-forward neural network (MFNN) model and an Echo State Network (ESN) model. First, the linear model is developed by linearizing a given nonlinear model and is analyzed as a function of the operating point. Second, the MFNN and the ESN are developed by using training data from the nonlinear model. The three models are validated using Matlab with nonlinear input-output data that was not used during training.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
• /
• pp.185-189
• /
• 1998

This paper addresses analysis and design of a fuzzy model-based-controller for the control of uncertain SISO nonlinear systems. In the design procedure, we represent the nonlinear system by using a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller via parallel distributed compensation and sliding mode control. Unlike other parallel distributed controllers, this globally stable fuzzy controller is designed without finding a common positive definite matrix for a set of Lyapunov equations, and has good tracking performance. The stability analysis is conducted not for the fuzzy model but for the real underlying nonlinear system. Furthermore, the proposed method can be applied to partially known uncertain nonlinear systems. A numerical simulation is performed for the control of an inverted pendulum, to show the effectiveness and feasibility of the proposed fuzzy control method.

• Structural Engineering and Mechanics
• /
• 제60권6호
• /
• pp.1039-1061
• /
• 2016

Based on Vlasov's torsional theory of open thin-walled members and the nonlinear constitutive relations of materials, a nonlinear analysis model to predict response of open thin-walled RC members subjected to pure torsion is proposed in the current study. The variation of the circulatory torsional stiffness and warping torsional stiffness over the entire loading process and the impact of warping shear deformation on the torsion-induced rotation of the member are considered in the formulation. The torque equilibrium differential equation is then solved by Runge-Kutta method. The proposed nonlinear model is then applied to predict the behavior of five U-shaped thin-walled RC members under pure torsion. Four of them were tested in an earlier experimental study by the authors and the testing data of the fifth one were reported in an existing literature. Results show that the analytical predictions based on the proposed model agree well with the experimental data of all five specimens. This clearly shows the validity of the proposed nonlinear model analyzing behavior of U-shaped thin-walled RC members under pure torsion.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
• /
• pp.191-194
• /
• 2007

The paper clarifies all the noise sources of a CMOS image sensor, with which the GOCI (Geostationary Ocean Color Imager) is equipped, and analyzes their contribution to a nonlinear image sensor model. In particular, the noise PDF (Probability Density Function) is derived in terms of sensor-gain coefficients: a linear and a nonlinear gains. As a result, the relation between the noise characteristic and the sensor gains is studied.