• Structural Engineering and Mechanics
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• v.48 no.2
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• pp.151-171
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• 2013

The current paper presents the numerical blind prediction of nonlinear seismic response of two full-scale, three dimensional, one-story reinforced concrete structures subjected to bidirectional earthquake simulations on shaking table. Simulations were carried out at the laboratories of LNEC (Laboratorio Nacional de Engenharia Civil) in Lisbon, Portugal. The study was motivated by participation in the blind prediction contest of shaking table tests, organized by the challenge committee of the 15th World Conference on Earthquake Engineering. The test specimens, geometrically identical, designed for low and high ductility levels, were subjected to subsequent earthquake motions of increasing intensity. Three dimensional nonlinear analytical models were implemented and subjected to the input base motions. Reasonably accurate reproduction of the measured displacement response was obtained through appropriate modeling. The goodness of fit between analytical and measured results depended on the details of the analytical models.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.187-193
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• 2003

In this paper, a systematic design method of the intelligent PAM fuzzy controller for nonlinear systems using the efficient tools-Linear Matrix Inequality and the intelligent digital redesign is proposed. In order to digitally control the nonlinear systems, the TS fuzzy model is used for fuzzy modeling of the given nonlinear system. The convex representation technique also can be utilized for obtaining TS fuzzy models. First, the analog fuzzy-model-based controller is designed such that the closed-loop system is globally asymptotically stable in the sense of Lyapunov stability criterion. The simulation results strongly convince us that the proposed method has great potential in the application to the industry.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.50-55
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• 1998

The GMDH(Group Method of Data Handling) is a useful data analysis technique for identification of nonlinear complex systems. Therefore, in this paper the application method of GMDH algorithm for modeling nonlinear dynamic systems is proposed. The identification of dynamic systems by using GMDH consists of applying a set of input/output data and computing the necessary coefficient set dynamically. Also, in this paper, by reducing sequentially the criterion which can adopt or reject the data, a method to prevent excessive computation that is a disadvantage of GMDH is proposed.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.175-180
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• 2005

Incorrections between model and plant are parameter, system order uncertainties and modeling error due to disturbance like friction. Therefore to achieve a good tracking performance, adaptive discrete time sliding mode tracking controller is used under time-varying desired position. Based on the diophantine equation, a new discrete time sliding function is defined and utilized for the control law. Robustness is increased by using both a recursive least-square method and a sliding function-based nonlinear feedback. The effectiveness of the proposed control algorithm is proved by the results of simulation and experiment.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.425-427
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• 1997

In this paper, a new approach to modeling and control of nonlinear systems using fuzzy theory is presented. To express the various and complex behavior of nonlinear system, we combine multiple model method with hierachical prioritized structure. The mountain clustering technique is used in partitioning of system, and TSK rule structure is adopted to form the fuzzy rules. Also we soften the paradigm of Mamdani's inference mechanism by using Yager's S-OWA operators.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.801-803
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• 1995

This paper presents the linearized fuzzy modeling technique of nonlinear dynamical system and the stability analysis of fuzzy control system. Firstly, the nonlinear system is partitionized by multiple linear fuzzy subcontrol systems based on fuzzy linguistic variables and fuzzy rules. Secondly, the disturbance adaptation controllers which guarrantee the global asymptotic stability of each fuzzy subsystem by an optimal feedback control law are designed and the stability analysis procedures of the total fuzzy control system using Lyapunov functions and eigenvalues are discussed in detail through a given illustrative example.

• Journal of Magnetics
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• v.22 no.2
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• pp.196-202
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• 2017

The occurrence of ferroresonance in electrical systems including nonlinear inductors such as transformers will bring a lot of malicious damages. The intense ferromagnetic saturation of the iron core is the most influential factor in ferroresonance that makes nonsinusoidal current and voltage. So the nonlinear behavior modeling of the magnetic core is the most important challenge in the study of ferroresonance. In this paper, the ferroresonance phenomenon is investigated in a single phase transformer using the finite element method and considering the hysteresis loop. Jiles-Atherton (JA) inverse vector model is used for modeling the hysteresis loop, which provides the accurate nonlinear model of the transformer core. The steady-state analysis of ferroresonance is done while considering different capacitors in series with the no-load transformer. The accurate results from copper losses and iron losses are extracted as the most important specifications of transformers. The validity of the simulation results is confirmed by the corresponding experimental measurements.

• International Journal of Automotive Technology
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• v.7 no.1
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• pp.91-99
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• 2006

The diesel Auxiliary Power Unit (APU) for vehicle applications is a complex nonlinear system. For the purpose of this paper presents a dynamic average model of the whole system in an entirely physical way, which accounts for the non-ideal behavior of the diode rectifier, the nonlinear phenomena of generator-rectifier set in an elegant way, and also the dynamics of the dc load and diesel engine. Simulation results show the accuracy of the model. Based on the average model, a simple PI control scheme is proposed for the multivariable system, which includes the steps of model linearization, separate PI controller design with robust tuning rules, stability verification of the overall system by considering it as an uncertain one. Finally it is tested on a detailed switching model and good performances are shown for both set-point following and disturbance rejection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.5
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• pp.667-675
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• 2002

In this Paper, we present a new nonlinear active noise control scheme using neural networks. Two neural network4 are used, one is for the active controller and another one is for the secondary path model. This scheme is suitable for the plant which has time-varing secondary path dynamics, because the secondary path modeling is performed via on-line fashion. Simulation results of active noise control with nonlinear primary/secondary path are presented. The results show that the new algorithm can reduce the noise level greatly.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.1
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• pp.171-177
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• 2002

The viscoelastic dampers are considered to be one of the most efficient means of upgrading existing structures against seismic loads. Generally in the dynamic analysis of a structure with added viscoelastic dampers the internal forces of the dampers are represented by constants that are linearly proportional to displacement and velocity. The purpose of this study is to verify the validity of the linear Kelvin model by comparing the results from the linear analysis with those obtained from the more rigorous nonlinear model such as fractional derivative model. According to the results the structural responses of 1-DOF structure obtained using the linear model are very close to those obtained from nonlinear model. However for multi-D0F structure the difference between the results from both models is enlarged as a results of the assumptions associated with the linear modeling of the viscoelastic dampers.