• Journal of Korean Society of Forest Science
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• v.84 no.1
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• pp.63-70
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• 1995

This paper discusses applications of neural network to stand stocking control problems. The scope of this research was to develop a neural network model for finding optimal stand management regimes and examining the performance of the model for field application. Performance was analyzed in consideration of the number of training examples and structural aspects of neural network. Research on network performance was based on extensive optimization studies for pure longleaf pine(Pinus palustris) stands. For experimental purposes. an existing nonlinear even-aged stand optimization model with a whole-stand growth and yield simulator was used to generate data samples required for the performance analysis.

• Journal of Navigation and Port Research
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• v.31 no.8
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• pp.697-703
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• 2007

In this paper, we focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. A T-S fuzzy model is characterized by fuzzy "if-then" rules which represent the locally input-output relationship whose consequence part is described by a state space equation as subsystem. The T-S fuzzy model in container cranes first obtains a few number of linear models according to operation conditions and blends these conditions using fuzzy membership functions. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear system of a container crane. Simulations are given to illustrate the performance of T-S fuzzy model.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.6
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• pp.730-736
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• 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.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.5
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• pp.377-388
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• 2016

This study is aimed to evaluate the embedment effect of foundation as compared to the surface foundation on the response of a base-isolated nuclear power plant structure. For this purpose, the boundary reaction method (BRM), which is a two-step frequency domain and time domain technique, is used for the nonlinear SSI analysis considering nonlinear behavior of base isolators. The numerical model of the BRM is verified by comparing the numerical results obtained by the BRM and the conventional frequency-domain SSI analysis for an equivalent linear SSI system. Finally, the displacement response of the base isolation and the horizontal response of the structure obtained by the nonlinear SSI analysis using the moat foundation model are compared with those using the surface foundation model. The comparison showed that the displacement response of the base isolation can be reduced by considering the embedment effect of foundation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.46-54
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• 1998

This paper presents a method for designing robust fuzzy $H^{\infty}$ controllers which stabilize nonlinear systems with parameter uncertainty adn guarantee an induced $L_{2}$ norm bound constraint on disturbance attenuation for all admissible uncertainties. Takagi and Sugeno's fuzzy models with uncertainty are used as the model for the uncertain nonlinear systems. Fuzzy control systems utilize the concept of so-called parallel distributed compensation(PDC). Using a single quadratic Lyapunov function, the stability condition satisfying decay rate and disturbance attenuation condition for Takagi and Sugeno's fuzzy model with parameter uncertainty are discussed. A sufficient condition for the existence of robust fuzzy $H^{\infty}$ controllers is then presented in terms of linear matrix inequalities(LMIs). Finally, design examples of robust fuzzy $H^{\infty}$ controllers for uncertain nonlinear systems are presented.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.3
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• pp.53-60
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• 2008

Recently, various recording technologies are studied for optical data storage. After standardization of BD (Blue-ray Disc) and HD-DVD (High-Definition Digital Versatile Disc), the industry is looking for a suitable technology for next generation optical data storage. Super-RENS (Super-resolution near field structure) technique, which is capable of compatibility with other systems, is one of next optical data storage. In this paper, we analyze the nonlinearity of Super-RENS read-out signal through the bicoherence test, which uses HOS (Higher-Order Statistics) and apply neural networks for nonlinear modeling. The model structure considered in this paper is the NARX (Nonlinear AutoRegressive eXogenous) model. The experiment results indicate that the read-out signals have nonlinear characteristics. In addition, it verified the possibility that neural networks can be utilized for nonlinear modeling of Super-RENS systems.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.73-79
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• 2009

For the shake of control for movement object, control theory like neural network, nonlinear model predictive control(NMPC) is realized on digital high speed computer. Predictor of flight control system(FCS) based nonlinear model predictive control has to be satisfied with response for hard real-time to perform applications on each module in the FCS. Simultaneously, It gives a serious consideration accuracy to give full play to FCS's performance. Error of mathematical aspect affects realization of whole algorithm. But factors of bring mathematical error is not considered to calculate final accuracy on parameter of predictor. In this paper, Predictor was made using load control model on the digital computer for design FCS at hard real-time and is shown response time on realization algorithm. And is shown realization algorithm of high effective predictor over the accuracy. The predictor was realized on the load control model using Euler method, Heun method, Runge-Kutta and Taylor method.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.152-160
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• 2000

This paper addresses the analysis and design of fuzzy-model-based controller for nonlinear systems using extended PDC and optimal pole-placement schemes. In the design procedure, we represent the nonlinear system using a Takagi-Sugeno fkzy model and formulate the controller rules by using the extended parallel distributed compensator (EPDC) and construct an overall fuzzy logic controller by blending all local state feedback controllers with an optimal pole-placement scheme. Unlike the commonly used parallel distributed compensation technique, by blending a newly extended parallel distributed compensator and the optimal poleplacement schemes, we can design not only a local stable k z y controller but also an overall stable fuzzy controller to perform the tacking control objective. Furthermore, a stability analysis is carried out not only for the fuzzy model but also for a real nonlinear system. Finally. the effectiveness and feasibility of the proposed fizzy model-based controller design method has been shown through a simulation example.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.202-208
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• 2014

Friction force on robot systems is highly nonlinear and especially disturbs precise control of the robots at low speed. This paper deals with the dynamic friction compensation problem of a well-known one-link benchmark robot system. We consider the LuGre model because the model can successfully represent dynamic characteristics and various effects of friction phenomenon. The proposed controller is constructed as two parts. An adaptive controller based on dual observers is used to estimate and compensate the dynamic friction. In order to attenuate the friction estimation error and other disturbances, PI observer is additionally designed. Through the computer simulations with the benchmark system, this paper first examines the effects of nonlinear dynamic friction on the control performance of the benchmark robot system. Next, it is shown that the control performance against the dynamic friction is improved by using the proposed controller.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1753_1754
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• 2009

본 논문은 한국 철도기술연구원에서 바이모달 트램의 안내/추진/도킹 제어기 검증을 위해 제작중인 LabVIEW, PXI기반의 실시간 시뮬레이터를 위한 시뮬레이션 프로그램 개발에 대한 내용을 다루었다. 시뮬레이터 프로그램은 바이모달 트램의 비선형 동적모델, 위치추정필터, 안내/추진/도킹 제어기로 구성되며, 비선형 동적모델에는 실제 차량에서 제어기나 관측기에 사용되는 각종 측정값들을 모사하기 위한 센서 계측시스템이 포함된다.