• Title/Summary/Keyword: nonlinear dynamic system

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Probabilistic Method for The Harmonic Analysis of Railroad Feeding System (철도급전시스템의 고조파 평가를 위한 확률론적 방법)

  • Lee, Seung-Hyuk;Song, Hak-Seon;Lee, Jun-Kyong;Kim, Jin-O
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.55 no.9
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    • pp.384-391
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    • 2006
  • The harmonic currents generated along with the operating speed of electrical railroad traction are very difficult to analyze because of its nonlinear characteristics. This paper therefore presents probabilistic approach for the evaluation of harmonic currents about the operating speed of the arbitrary single traction. To use probabilistic method for railroad system, PDF(Probability Density Function) using measuring data based on the realistic h 따 monic currents per operating speed is calculated. Measuring data of harmonic current per operating speed is obtained using the result data of PSCAD/EMTDC dynamic simulation based on an IAT(Intra Airport Transit) in Incheon International Airport. The means(expected values) and variances of harmonic currents of single traction also are obtained by the PDF of the operating traction speed and harmonic currents. The uncertainty of harmonic currents can be calculated through the mean and variance of PDF. The probability of harmonic currents generated with the operating of arbitrary many tractions is calculated by the convolution of functions. The harmonics of different number of tractions are systematically investigated to assess the TDD(Total Demand Distortion) for the railroad system. The calculation of TDD was carried out using Monte-Carlo Simulations(MSCs) and the results of TDD evaluation of the power quality in the IAT power feeding system.

System Identification Using Gamma Multilayer Neural Network (감마 다층 신경망을 이용한 시스템 식별)

  • Go, Il-Whan;Won, Sang-Chul;Choi, Han-Go
    • Journal of the Institute of Convergence Signal Processing
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    • v.9 no.3
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    • pp.238-244
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    • 2008
  • Dynamic neural networks have been applied to diverse fields requiring temporal signal processing. This paper presents gamma neural network(GAM) to improve the dynamics of multilayer network. The GAM network uses the gamma memory kernel in the hidden layer of feedforword multilayer network. The GAM network is evaluated in linear and nonlinear system identification, and compared with feedforword(FNN) and recurrent neural networks(RNN) for the relative comparison of its performance. Experimental results show that the GAM network performs better with respect to the convergence and accuracy, indicating that it can be a more effective network than conventional multilayer networks in system identification.

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Inelastic Transient Dynamic Analysis of Two- and Three-dimensional Stress Problems by Particular Integral Boundary Element Method (로터 시스템 회전운동의 정식화 및 해석)

  • Yun, Seong-Ho;Ren, Li-Min
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.21 no.5
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    • pp.475-482
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    • 2008
  • This paper indicates that the use of Euler angles lacks in its consistency and exactness of analysis when it was applied to incorporate the rotational equation of motion for rotor systems by previous researcher. Kinetic energy and angular velocity are different from case to case depending on the way of choosing Euler angles and thus only the linear system has been investigated even though the rotor system has a very nonlinear behavior. A new methodology is applied by using both spherical coordinate and quaternion in the rotor rotation to overcome weaknesses of Euler angles and shows its superiority It is found through numerical examples that the use of quaternion will be a more useful and valid tool to derive the numerical model of the rotor system.

Seismic performance of a resilient low-damage base isolation system under combined vertical and horizontal excitations

  • Farsangi, Ehsan Noroozinejad;Tasnimi, Abbas Ali;Yang, T.Y.;Takewaki, Izuru;Mohammadhasani, Mohammad
    • Smart Structures and Systems
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    • v.22 no.4
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    • pp.383-397
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    • 2018
  • Traditional base isolation systems focus on isolating the seismic response of a structure in the horizontal direction. However, in regions where the vertical earthquake excitation is significant (such as near-fault region), a traditional base-isolated building exhibits a significant vertical vibration. To eliminate this shortcoming, a rocking-isolated system named Telescopic Column (TC) is proposed in this paper. Detailed rocking and isolation mechanism of the TC system is presented. The seismic performance of the TC is compared with the traditional elastomeric bearing (EB) and friction pendulum (FP) base-isolated systems. A 4-storey reinforced concrete moment-resisting frame (RC-MRF) is selected as the reference superstructure. The seismic response of the reference superstructure in terms of column axial forces, base shears, floor accelerations, inter-storey drift ratios (IDR) and collapse margin ratios (CMRs) are evaluated using OpenSees. The results of the nonlinear dynamic analysis subjected to multi-directional earthquake excitations show that the superstructure equipped with the newly proposed TC is more resilient and exhibits a superior response with higher margin of safety against collapse when compared with the same superstructure with the traditional base-isolation (BI) system.

A Study on Improving the Accuracy of Finite Element Modeling Using System Identification Technique (S. I. 기법을 이용한 유한요소모델의 신뢰도 제고에 관한 연구)

  • 양경택
    • Computational Structural Engineering
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    • v.10 no.2
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    • pp.149-160
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    • 1997
  • Mechanical structures are composed of substructures connected by joints and boundary elements. While the finite element representation of plain substructures is well developed and reliable, joints have a lot of uncertainties in being accurately modelled and affect dynamic behavior of a total system. In order to improve the accuracy of a finite element model, a new method is proposed, in which reduced finite element model is combined with a system identification technique. After substructures except joints are modelled with finite element method and joint properties are represented by parameter states, non-linear state equation is derived in which parameter states are multiplied by physical states such as displacements and velocities. So the joint parameter identification is transformed into non-linear state estimation problem. The methods are tested and discussed numerically and the feasibility for physical application has been demonstrated through two example structures.

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A Neural Network Aided Kalman Filtering Approach for SINS/RDSS Integrated Navigation

  • Xiao-Feng, He;Xiao-Ping, Hu;Liang-Qing, Lu;Kang-Hua, Tang
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.491-494
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    • 2006
  • Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.

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Improved Trigger System for the Suppression of Harmonics and EMI Derived from the Reverse-Recovery Characteristics of a Thyristor

  • Wei, Tianliu;Wang, Qiuyuan;Mao, Chengxiong;Lu, Jiming;Wang, Dan
    • Journal of Power Electronics
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    • v.17 no.6
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    • pp.1683-1693
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    • 2017
  • This paper analyses the harmonic pollution to power grids caused by thyristor-controlled devices. It also formulates a mathematic derivation for the voltage spikes in thyristor-controlled branches to explain the harmonic and EMI derived from the reverse-recovery characteristics of the thyristor. With an equivalent nonlinear time-varying voltage source, a detailed simulation model is established, and the periodic dynamic switching characteristic of the thyristor can be explicitly implied. The simulation results are consistent with the probed results from on-site measurements. An improved trigger system with gate-shorted circuit structure is proposed to reduce the voltage spikes that cause EMI. The experimental results indicate that a prototype with the improved trigger system can effectively suppress the voltage spikes.

Application of black box model for height prediction of the fractured zone in coal mining

  • Zhang, Shichuan;Li, Yangyang;Xu, Cuicui
    • Geomechanics and Engineering
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    • v.13 no.6
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    • pp.997-1010
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    • 2017
  • The black box model is a relatively new option for nonlinear dynamic system identification. It can be used for prediction problems just based on analyzing the input and output data without considering the changes of the internal structure. In this paper, a black box model was presented to solve unconstrained overlying strata movement problems in coal mine production. Based on the black box theory, the overlying strata regional system was viewed as a "black box", and the black box model on overburden strata movement was established. Then, the rock mechanical properties and the mining thickness and mined-out section area were selected as the subject and object respectively, and the influences of coal mining on the overburden regional system were discussed. Finally, a corrected method for height prediction of the fractured zone was obtained. According to actual mine geological conditions, the measured geological data were introduced into the black box model of overlying strata movement for height calculation, and the fractured zone height was determined as 40.36 m, which was comparable to the actual height value (43.91 m) of the fractured zone detected by Double-block Leak Hunting in Drill. By comparing the calculation result and actual surface subsidence value, it can be concluded that the proposed model is adaptable for height prediction of the fractured zone.

Development of a seismic retrofit system made of steel frame with vertical slits

  • Kang, Hyungoo;Adane, Michael;Chun, Seungho;Kim, Jinkoo
    • Steel and Composite Structures
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    • v.44 no.2
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    • pp.283-294
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    • 2022
  • In this study, a new seismic retrofit scheme of building structures is developed by combining a steel moment frame and steel slit plates to be installed inside of an existing reinforced concrete frame. This device has the energy dissipation capability of slit dampers with slight loss of stiffness compared to the conventional steel frame reinforcement method. In order to investigate the seismic performance of the retrofit system, it was installed inside of a reinforced concrete frame and tested under cyclic loading. Finite element analysis was carried out for validation of the test results, and it was observed that the analysis and the test results match well. An analytical model was developed to apply the retrofit system to a commercial software to be used for seismic retrofit design of an example structure. The effectiveness of the retrofit scheme was investigated through nonlinear time-history response analysis (NLTHA). The cyclic loading test showed that the steel frame with slit dampers provides significant increase in strength and ductility to the bare structure. According to the analysis results of a case study building, the proposed system turned out to be effective in decreasing the seismic response of the model structure below the given target limit state.

Smart tracking design for aerial system via fuzzy nonlinear criterion

  • Wang, Ruei-yuan;Hung, C.C.;Ling, Hsiao-Chi
    • Smart Structures and Systems
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    • v.29 no.4
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    • pp.617-624
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    • 2022
  • A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.