• Journal of Mechanical Science and Technology
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• 제20권11호
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• pp.1813-1822
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• 2006

The dynamic analysis of a plate with non-linearity due to large deformation was investigated in this study. There have been many theoretical and numerical analyses of the non-linear dynamic behavior of plates examining theoretically or numerically. The problem is how correctly an analytical model can represent the dynamic characteristics of the actual system. To address the issue, the continuous-time system identification technique was used to generate non-linear models, for stiffness and damping terms, and to explain the observed behaviors with single mode assumption after comparing experimental results with the numerical results of a linear plate model.

• Journal of applied mathematics & informatics
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• 제38권5_6호
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• pp.469-481
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• 2020

In this paper, we consider a control system for semilinear differential equations in Hilbert spaces with Lipschitz continuous nonlinear term. Our method is to find the equivalence of approximate controllability for the given semilinear system and the linear system excluded the nonlinear term, which is based on results on regularity for the mild solution and estimates of the fundamental solution.

• 한국생산제조학회지
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• 제8권4호
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• pp.112-122
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• 1999

In realistic control systems the nonlinear saturation attributes of the control actuator due to physical limitations should be taken into account This nonlinear saturation of actuators may cause not only deterioration of the control performance but also a large overshoot during start-up and shut-down. As the overshoot increases the system may become oscillatory unstable. in this paper the supervisor implementation which guarantees good performance for saturation operation and prevents reset wind up is presented, Moreover the sufficient conditions of the stability for saturated system using supervisory control with a dynamic controller are provided in the continuous-time and in the discrete-time domain Numerical example is illustrated to depict the efficiency of supervisory control for a typical satuaurated production-distribution system controlled by a discrete-time dynamic controller and to validate basic results by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.14-19
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• 1993

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.

• 콘크리트학회논문집
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• 제23권2호
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• pp.177-184
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• 2011

이 연구에서는 PC 구조의 단부를 연속으로 연결한 MRS(multi-ribbed moment resisting slab) 구조에 대한 해석 및 설계법을 제안하고자 하였다. MRS 구조에서는 더블티 부재가 역티보 위에서 부모멘트 철근에 의해서 연속으로 설계되므로, 부모멘트 철근이 좁은 지역에 밀집되는 문제가 발생할 수 있다. 따라서 선형 및 비선형 해석을 통하여 모멘트 분포 메커니즘을 분석하여, 적절한 설계법을 제시하였다. 또한 이 연구와 병행하여 실시한 실험 연구의 결과를 비선형상세 해석을 통하여 분석하였다. 그리고 단부구속효과 및 모멘트 재분배에 관한 연구를 위하여 비선형 골조 해석을 선택하여 변수별 연구를 수행하였다. 해석을 위한 재질 및 단면의 특성은 함께 진행된 실험 연구의 결과로부터 얻어졌으며, 비선형 골조 해석을 위한 소성힌지는 균열 모멘트, 공칭 모멘트, 부재 연성도 등의 값으로 모델링되었다. 선형 및 비선형 해석의 결과로부터 단부 회전 스프링과 부모멘트재분재를 통하여 MRS 구조의 단부 모멘트는 상당한 크기로 감소시킬 수 있음을 알 수 있었다.

• Transactions on Control, Automation and Systems Engineering
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• 제4권4호
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• pp.277-282
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• 2002

This paper proposes a nonlinear adaptive controller based on back-stepping method for tracking reference substrate concentration by manipulating dilution rate in a continuous baker's yeast cultivating process in stirred tank bioreactor. Control law is obtained from Lyapunov control function to ensure asymptotical stability of the system. The Haldane model for the specific growth rate depending on only substrate concentration is used in this paper. Due to the uncertainty of specific growth rate, it has been modified as a function including the unknown parameter with known bounded values. The substrate concentration in the bioreactor and feed line are measured. The deviation from the reference is observed when the external disturbance such as the change of the feed is introduced to the system. The effectiveness of the proposed controller is shown through simulation results in continuous system.

• 전자공학회논문지S
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• 제34S권9호
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• pp.41-49
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• 1997

In this paper, we describe the algorithm which controls an unknown nonlinear system with disturbance a using multilayer neural network. The multilayer neural network can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate an unknown nonlinear system by using of multilayer neural netowrk. WE include a disturbance among the modelling error, and the weight-update rule of multilayer neural network is derived to satisfy Laypunov stability. The whole control system constitutes controller using the feedback linearization method. The weight of neural network which is used to implement nonlinear function is updated by the derived update-rule. The proposed control algorithm is verified through computer simulation.

• 대한기계학회논문집
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• 제18권2호
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• pp.372-379
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• 1994

In this study, the describing function is adopted to represent nonlinearity in the system equations. The compliance can be obtained by solving nonlinear simultaneous algebraic quations for multi-degrees-of-freedom system with multinonlinearities. When the technique is applied, the nonlinearity of the system can be identified from the compliance which is obtained from the sinusoidal excitation of the system. By employing the describing function in the Building Block Analysis, we can extensively develop the BBA into investigation of the continuous systems with nonlinearities. The evaluated compliance can quantitatively show the effects of nonlinearity such as the transfer of the natural frequency, the variance of the compliance at the natural frequency, and the jump phenomena which occur during sweeping of the excitation frequency.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2034-2036
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• 2002

In this paper, we propose the modeling of a chaotic nonlinear system using wavelet neural networks. In our modeling, we used the parameter adjusting method as the training method of a wavelet neural network. The difference between the actual output of a nonlinear chaotic system and that of a wavelet neural network adjusts the parameters of a wavelet neural network using the gradient-descent method. To verify the efficiency of this paper, we perform the simulation using Duffing system, which is a representative continuous time chaotic nonlinear system.

• 전자공학회논문지B
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• 제33B권7호
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• pp.32-39
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• 1996

In this paper, we describe the algorithm which controls an unknown nonlinear system with multilayer neural network. The multilayer neural netowrk can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate unknown nonlinear function on the nonlinear system by using of multilayer neural netowrk. The weights on the hidden layer of multilayer neural network are updated by gradient method. The weight-update rule on the output layer is derived to satisfy lyapunov stability. Also, we obtain secondary controller form deriving step. The global control system consists of controller using feedback linearization method and secondary controller is order to satisfy layapunov stability. The proposed control algorithm is verified through computer simulation.