• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.4
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• pp.105-112
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• 2005

Analyses of dynamic models which were one and two degrees of freedom, and had the nonlinear springs and dampings with certain polynomial functions were performed from SIMULINK in MATLAB. Those consisted of 12 programs and were built on the basis of the preceding programs fur the linear dynamic simulations. However the programs for the nonlinear simulations were quite different from those f3r the linear ones, and showed the results of the analyses in real time with animating. It was found that the programs would help us to solve any kind of nonlinear dynamic simulation with one and two degrees of freedom. Especially, the simulations for 1 DOF system with cubic nonlinear spring farce showed the results for Duffing's equation, of which phenomena were jump-up and jump-down. It will be applied to the dynamic simulation of the car seat vibration with a passenger, of which model has the equivalent nonlinear springs and is two degrees of freedom.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.189-199
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• 1999

This paper presents an optimization algorithm for a stable Self Dynamic Neural Network(SDNN) using genetic algorithm. Optimized SDNN is applied to a problem of controlling nonlinear dynamical systems. SDNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real-time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDW has considerably fewer weights than DNN. Since there is no interlink among the hidden layer. The object of proposed algorithm is that the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling a nonlinear dynamic system using the proposed optimized SDNN considering stability is demonstrated by case studies.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.12
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• pp.19-26
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• 1991

In this paper, we give a structure algorithm for the synthesis problems of the nonlinear system via dynamic feedback. Using our algorithm, sufficient conditions for the input-output synthesis problems are discussed. The problems we consider in this paper include dynamic input-output decoupling input-output linearization, and immersion into a linear system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1188-1194
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• 1997

In this paper, we design output feedback nonlinear dynamic control law by using state feedback nonlinear dynamic compensator and PI observer and show that the controller can stabilize globally and asymptotically a class of nonlinear systems with mismatched uncertainties. We also show that it is possible for a nonlinear system to use the output of PI observer in place of state variables in case that the nonlinear dynamic control law is used, similarly as in the linear system. The effectiveness of the proposed control law is demonstrated by a numerical simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1184-1184
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• 1997

In this paper, we design output feedback nonlinear dynamic control law by using state feedback nonlinear dynamic compensator and PI observer and show that the controller can stabilized globally and asymptotically a class of nonlinear systems with mismatched uncertainties. We also show that it is possible for a nonlinear system to use the output of PI observer in place of state variables in case that the nonlinear dynamic control law is used, similarly as in the linear system. The effectiveness of the proposed control law is demonstrated by a numerical simulation.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.3
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• pp.697-704
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• 1995

The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents the stochastic model of a nonlinear dynamic system with uncertain parameters under nonstationary stochastic inputs. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method and the second moment equation is numerically evaluated by stochastic process closure method, 4th cumulant neglect closure method and Runge-Kutta method. But the first and the second moment equations are coupled each other, so this equations are approximately evaluated by a iterative method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

• Journal of Mechanical Science and Technology
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• v.15 no.11
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• pp.1507-1516
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• 2001

An analytical method is presented for evaluation of the steady state periodic behavior of nonlinear structural systems. This method is based on the substructure synthesis formulation and a harmonic balance procedure, which is applied to the analysis of nonlinear responses. A complex nonlinear system is divided into substructures, of which equations are approximately transformed to modal coordinates including nonlinear term under the reasonable procedure. Then, the equations are synthesized into the overall system and the nonlinear solution for the system is obtained. Based on the harmonic balance method, the proposed procedure reduces the size of large degrees-of-freedom problem in the solving nonlinear equations. Feasibility and advantages of the proposed method are illustrated using the study of the nonlinear rotating machine system as a large mechanical structure system. Results obtained are reported to be an efficient approach with respect to nonlinear response prediction when compared with other conventional methods.

• 전기의세계
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• v.16 no.3
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• pp.16-20
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• 1967

To analyze the stability creterion and the dynamic performance of the nonlinear reactor control system which involve the on-off element and gear backlash, the concept of discribing function is developed for the system of two nonlinear elements are connected by linear element. Using the derived discribing function and frequency responce method, the stability creterion and the dynamic performance of the nonlinear reactor control system are analyzed, and the results of the analysis are conformed by analog computor.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.384-384
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• 2000

In adaptive neuro-control, neural networks are used to approximate the unknown plant nonlinearities. Until now, most of the papers in the field of controller design fur nonlinear system using neural networks considers the affine system with fixed number of neurons. This paper considers nonaffne nonlinear systems and dynamic variation of the number of neurons. Control laws and adaptive laws for weights are established so that the whole system is stable in the sense of Lyapunov.

• Coupled systems mechanics
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• v.1 no.1
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• pp.39-57
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• 2012

This study intends to explore dynamic interaction behaviors between actively controlled maglev vehicle and guideway girders by considering the nonlinear forms of electromagnetic force and current exactly. For this, governing equations for the maglev vehicle with ten degrees of freedom are derived by considering the nonlinear equation of electromagnetic force, surface irregularity, and the deflection of the guideway girder. Next, equations of motion of the guideway girder, based on the mode superposition method, are obtained by applying the UTM-01 control algorithm for electromagnetic suspension to make the maglev vehicle system stable. Finally, the numerical studies under various conditions are carried out to investigate the dynamic characteristics of the maglev system based on consideration of the linear and nonlinear electromagnetic forces. From numerical simulation, it is observed that the dynamic responses between nonlinear and linear analysis make little difference in the stable region. But unstable responses in nonlinear analysis under poor conditions can sometimes be obtained because the nominal air-gap is too small to control the maglev vehicle stably. However, it is demonstrated that this unstable phenomenon can be removed by making the nominal air-gap related to electromagnetic force larger. Consequently it is judged that the nonlinear analysis method considering the nonlinear equations of electromagnetic force and current can provide more realistic solutions than the linear analysis.