• 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 the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.53-60
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• 2007

This paper presents a robust nonlinear autopilot design method based on dynamic inversion and PI(Proportional-Integral) control law. The new controller structure which is different from previous work is composed of classical linear PI control law and nonlinear fast dynamic inversion. A pitch axis model of highly maneuverable missiles and a linearized model for designing Pl controller are presented. The performance of proposed method is illustrated via nonlinear simulations including aerodynamic uncertainties and actuator dynamics.

• Earthquakes and Structures
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• v.12 no.3
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• pp.285-296
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• 2017

Base isolation is a quite practical control strategy for enhancing the response of structural systems induced by strong ground motions. Due to the dynamic effects of base isolation systems, reduction in the interstory drifts of the superstructure is often achieved at the expense of high base displacement level, which may lead to instability of the structure or non-practical designs for the base isolators. To reduce the base displacement, several hybrid structural control strategies have been studied over the past decades. This study investigates a particular strategy that employs Tuned Mass Dampers (TMDs) for improving the performance of base-isolated structures and unlike previous studies, specifically focuses on the effectiveness of this hybrid control strategy in structures that are equipped with nonlinear base isolation systems. To consider the nonlinearities of base isolation systems, a Bouc-Wen model is selected and nonlinear dynamic OpenSees models are used to perform several time-history simulations in time and frequency domains. Through these numerical simulations, the effects of several parameters such as the fundamental period of the structure, dynamic properties of the TMD and isolation systems and properties of the input ground motion on the behaviour of TMD-structure-base isolation systems are examined. The results of this study provide a better insight into the performance of linear shear-story structures with nonlinear base isolators and show that there are many scenarios in which TMDs can still improve the performance of these systems.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.04a
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• pp.180-189
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• 2001

In this study, recently developed unscented Kalman filter (UKF) technique is studied for identification of nonlinear structural dynamic systems as an alternative to the extended Kalman filter (EKF). The EKF, which was originally developed as a state estimator for nonlinear systems, has been frequently employed for parameter identification by introducing the state vector augmented with the unknown parameters to be identified. However, the EKF has several drawbacks such as biased estimations and erroneous estimations especially for highly nonlinear dynamic systems due to its crude linearization scheme. To overcome the weak points of the EKF, the UKF was recently developed as a state estimator. Numerical simulation studies have been carried out on nonlinear SDOF system and nonlinear MDOF system. The results from a series of numerical simulations indicate that the UKF is superior to the EKF in the system identification of nonlinear dynamic systems especially highly nonlinear systems.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.10a
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• pp.117-126
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• 2001

In this study, the recently developed unscented Kalman filter (UKF) technique is studied for identification of nonlinear structural dynamic systems as an alternative to the extended Kalman filter (EKF). The EKF, which was originally developed as a state estimator for nonlinear systems, has been frequently employed for parameter identification by introducing the state vector augmented with the unknown parameters to be identified. However, the EKF has several drawbacks such as biased estimations and erroneous estimations especially for highly nonlinear dynamic systems due to its crude linearization scheme. To overcome the weak points of the EKF, the UKF was recently developed as a state estimator. Numerical simulation studies have been carried out on nonlinear SDOF system and nonlinear MDOF system. The results from a series of numerical simulations indicate that the UKF is superior to the EKF in the system identification of nonlinear dynamic systems especially highly nonlinear systems.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.6
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• pp.97-108
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• 1996

A modeling technique is proposed for dynamic simulations of OHC valve trains with HLA(hydraulic lash adiuster). HLA is expressed by an air-oil mixture model considering HLA leak-down and aeraton effects. A compact nonlinear equation is derived which describe the short term dynamic behavior of the HLA. Valve spring is analyzed by a distributed parameter model including nonlinear characteristics in the spring surge phenomena. Global behavior of the remaining valve train is expressed by a lumped mass model. The experiental results prove that the simulation model developed here is accurate and useful for the dynamic simulations of OHC valve trains with HLA.

• Earthquakes and Structures
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• v.3 no.3_4
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• pp.341-363
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• 2012

The spectral representation method is a quick and versatile tool for the generation of spatially variable, response-spectrum-compatible simulations to be used in the nonlinear seismic response evaluation of extended structures, such as bridges. However, just as recorded data, these simulated accelerations require processing, but, unlike recorded data, the reasons for their processing are purely numerical. Hence, the criteria for the processing of acceleration simulations need to be tied to the effect of processing on the structural response. This paper presents a framework for processing acceleration simulations that is based on seismological approaches for processing recorded data, but establishes the corner frequency of the high-pass filter by minimizing the effect of processing on the response of the structural system, for the response evaluation of which the ground motions were generated. The proposed two-step criterion selects the filter corner frequency by considering both the dynamic and the pseudo-static response of the systems. First, it ensures that the linear/nonlinear dynamic structural response induced by the processed simulations captures the characteristics of the system's dynamic response caused by the unprocessed simulations, the frequency content of which is fully compatible with the target response spectrum. Second, it examines the adequacy of the selected estimate for the filter corner frequency by evaluating the pseudo-static response of the system subjected to spatially variable excitations. It is noted that the first step of this two-fold criterion suffices for the establishment of the corner frequency for the processing of acceleration time series generated at a single ground-surface location to be used in the seismic response evaluation of, e.g. a building structure. Furthermore, the concept also applies for the processing of acceleration time series generated by means of any approach that does not provide physical considerations for the selection of the corner frequency of the high-pass filter.

• Journal of Ocean Engineering and Technology
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• v.33 no.5
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• pp.400-410
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• 2019

In this study, the numerical code for the 3D nonlinear dynamic analysis of an SLWR (Steel Lazy Wave Riser) was developed using the lumped mass line model in a FORTRAN environment. Because the lumped mass line model is an explicit method, there is no matrix operation. Thus, the numerical algorithm is simple and fast. In the lumped mass line model, the equations of motion for the riser were derived by applying the various forces acting on each node of the line. The applied forces at the node of the riser consisted of the tension, shear force due to the bending moment, gravitational force, buoyancy force, riser/ground contact force, and hydrodynamic force based on the Morison equation. Time integration was carried out using a Runge-Kutta fourth-order method, which is known to be stable and accurate. To validate the accuracy of the developed numerical code, simulations using the commercial software OrcaFlex were carried out simultaneously and compared with the results of the developed numerical code. To understand the nonlinear dynamic characteristics of an SLWR, dynamic simulations of SLWRs excited at the hang-off point and of SLWRs in regular waves were carried out. From the results of these dynamic simulations, the displacements at the maximum bending moments at important points of the design, like the hang-off point, sagging point, hogging points, and touch-down point, were observed and analyzed.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1569-1572
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• 1997

In this paper, we present an associative memory network (AMN) controller for dynamic robot control. The purpose of using AMN is to reduce the size of required memory in storing and recalling large of daa representing input relationship of nonlinear functions. With the capability AMN can be used to dynamic robot control, which has nonlinear properties inherently. The proposed AMN control scheme has advantages for the inverse dynamics learning no limitatiion of inpur range, and insensitive of payload change. Computer simulations show the effectiveness and feasibility of proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.11
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• pp.968-973
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• 2000

Fault diagnosis plays an important role in the performance and safe operation of many modern engineering plants. This paper investigates the problem of fault detection using neural networks in dynamic systems. A general framework for constructing a nonlinear fault detection scheme for nonlinear dynamic systems containing modeling uncertaintly is proposed. The main idea behind the proposed approach is to monitor the physical system with an off -line learning neural network and then to approximate the upper and lower thresholds of acceleration of the nominal system with the model-based threshold(ThMB) method, The performance of the proposed fault detection scheme is investigated through simulations of a pendulum with uncertainty.