• Title/Summary/Keyword: Model Uncertainties

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Failure probability of tall buildings with TMD in the presence of structural, seismic, and soil uncertainties

  • Sadegh, Etedali;Mohammad, Seifi;Morteza, Akbari
    • Structural Engineering and Mechanics
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    • v.85 no.3
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    • pp.381-391
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    • 2023
  • The seismic performance of the tall building equipped with a tuned mass damper (TMD) considering soil-structure interaction (SSI) effects is well studied in the literature. However, these studies are performed on the nominal model of the seismic-excited structural system with SSI. Hence, the outcomes of the studies may not valid for the actual structural system. To address the study gap, the reliability theory as a useful and powerful method is utilized in the paper. The present study aims to carry out reliability analyses on tall buildings equipped with TMD under near-field pulse-like (NFPL) ground motions considering SSI effects using a subset simulation (SS) method. In the presence of uncertainties of the structural model, TMD device, foundation, soil, and near-field pulse-like ground motions, the numerical studies are performed on a benchmark 40-story building and the failure probabilities of the structures with and without TMD are evaluated. Three types of soils (dense, medium, and soft soils), different earthquake magnitudes (Mw = 7,0. 7,25. 7,5 ), different nearest fault distances (r = 5. 10 and 15 km), and three seismic performance levels of immediate occupancy (IO), life safety (LS), and collapse prevention (CP) are considered in this study. The results show that tall buildings built near faults and on soft soils are more affected by uncertainties of the structural and ground motion models. Hence, ignoring these uncertainties may result in an inaccurate estimation of the maximum seismic responses. Also, it is found the TMD is not able to reduce the failure probabilities of the structure in the IO seismic performance level, especially for high earthquake magnitudes and structures built near the fault. However, TMD is significantly effective in the reduction of failure probability for the LS and CP performance levels. For weak earthquakes and long fault distances, the failure probabilities of both structures with and without TMD are near zero, and the efficiency of the TMD in the reduction of failure probabilities is reduced by increasing earthquake magnitudes and the reduction of fault distance. As soil softness increases, the failure probability of structures both with and without TMD often increases, especially for severe near-fault earthquake motion.

The Controller Design for Lane Following with 3-Degree of Freedom Vehicle Dynamics (3자유도 차량모델을 이용한 차선추종 µ 제어기 설계)

  • Ji, Sang-Won;Lim, Tae-Woo;You, Sam-Sang;Kim, Hwan-Seong
    • Journal of Power System Engineering
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    • v.17 no.3
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    • pp.72-81
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    • 2013
  • Many articles have been published about a 2-degree of freedom model that includes the lateral and yaw motions for controller synthesis in intelligent transport system applications. In this paper, a 3-degree of freedom linear model that includes the roll motion is developed to design a robust steering controller for lane following maneuvers using ${\mu}$-synthesis. This linear perturbed system includes a set of parametric uncertainties in cornering stiffness and unmodelled dynamics in steering actuators. The state-space model with parametric uncertainties is represented in linear fractional transformation form. Design purpose can be obtained by properly choosing the frequency dependent weighting functions. The objective of this study is to keep the tracking error and steering input energy small in the presence of variations of the cornering stiffness coefficients. Furthermore, good ride quality has to be achieved against these uncertainties. Frequency-domain analyses and time-domain numerical simulations are carried out in order to evaluate these performance specifications of a given vehicle system. Finally, the simulation results indicate that the proposed robust controller achieves good performance over a wide range of uncertainty for the given maneuvers.

Robust High-Gain Observer Based SOC Estimator for Uncertain RC Model of Li-Ion Batteries (불확실성을 갖는 RC 모델 기반의 리튬이온 배터리 SOC 추정을 위한 강인한 고이득 관측기 설계)

  • Lee, Jong-Yeon;Kim, Wonho;Hyun, Chang-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.3
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    • pp.214-219
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    • 2013
  • This paper proposes the robust high-gain observer based SOC estimatro for uncertain RC model of Li-Ion batteries. In general, RC battery model has inevitable uncertainties and it cause some negative effect to estimate the accurate SOC of Li-Ion batteries. The proposed estimator overcomes such weakness with two techniques; high-gain observer design technique and sliding mode control technique. A high-gain observer provides the robustness against model uncertainties to the proposed estimator. A sliding mode control technique helps the proposed estimator by reducing the side effect of adopting a high-gain observer such as peaking phenomenon and perturbation. The performance of the proposed estimator is verified by some simulation.

Intelligent Digital Redesign for Dynamical Systems with Uncertainties (불확실성을 갖는 동적 시스템에 대한 지능형 디지털 재설계)

  • Cho, Kwang-Lae;Joo, Young-Hoon;Park, Jin-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.6
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    • pp.667-672
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    • 2003
  • In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may also contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear systems. An extended parallel distributed compensation(EPDC) technique is then used to design a fuzzy-model-based controller for both stabilization and tracking. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using an integrated intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, The single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

Modal-based model reduction and vibration control for uncertain piezoelectric flexible structures

  • Yalan, Xu;Jianjun, Chen
    • Structural Engineering and Mechanics
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    • v.29 no.5
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    • pp.489-504
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    • 2008
  • In piezoelectric flexible structures, the contribution of vibration modes to the dynamic response of system may change with the location of piezoelectric actuator patches, which means that the ability of actuators to control vibration modes should be taken into account in the development of modal reduction model. The spatial $H_2$ norm of modes, which serves as a measure of the intensity of modes to system dynamical response, is used to pick up the modes included in the reduction model. Based on the reduction model, the paper develops the state-space representation for uncertain flexible tructures with piezoelectric material as non-collocated actuators/sensors in the modal space, taking into account uncertainties due to modal parameters variation and unmodeled residual modes. In order to suppress the vibration of the structure, a dynamic output feedback control law is designed by imultaneously considering the conflicting performance specifications, such as robust stability, transient response requirement, disturbance rejection, actuator saturation constraints. Based on linear matrix inequality, the vibration control design is converted into a linear convex optimization problem. The simulation results show how the influence of vibration modes on the dynamical response of structure varies with the location of piezoelectric actuators, why the uncertainties should be considered in the reductiom model to avoid exciting high-frequency modes in the non-collcated vibration control, and the possiblity that the conflicting performance specifications are dealt with simultaneously.

Parameter Optimization and Uncertainty Analysis of the Rainfall-Runoff Model (강우-유출모형 매개변수의 최적화 및 불확실성 분석)

  • Moon, Young-Il;Kwon, Hyun-Han
    • 한국방재학회:학술대회논문집
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    • 2008.02a
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    • pp.723-726
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    • 2008
  • It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established, uncertainty analysis, therefore, are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an expected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

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A New Approach to the Design of a Fuzzy Sliding Mode Controller for Uncertain Nonlinear Systems

  • Seo, Sam-Jun;Kim, Dong-Sik;Kim, Dong-Won;Yoo, Ji-Yoon;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.646-651
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    • 2004
  • This paper deals with a new adaptive fuzzy sliding mode controller and its application to an inverted pendulum. We propose new method of adaptive fuzzy sliding mode control scheme that the fuzzy logic system is used to approximate the unknown system functions in designing the SMC of uncertain nonlinear systems. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. Sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved

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Terminal Sliding Mode Control of Nonlinear Systems Using Self-Recurrent Wavelet Neural Network (자기 회귀 웨이블릿 신경망을 이용한 비선형 시스템의 터미널 슬라이딩 모드 제어)

  • Lee, Sin-Ho;Choi, Yoon-Ho;Park, Jin-Bae
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.11
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    • pp.1033-1039
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    • 2007
  • In this paper, we design a terminal sliding mode controller based on self-recurrent wavelet neural network (SRWNN) for the second-order nonlinear systems with model uncertainties. The terminal sliding mode control (TSMC) method can drive the tracking errors to zero within finite time in comparison with the classical sliding mode control (CSMC) method. In addition, the TSMC method has advantages such as the improved performance, robustness, reliability and precision. We employ the SRWNN to approximate model uncertainties. The weights of SRWNN are trained by adaptation laws induced from Lyapunov stability theorem. Finally, we carry out simulations for Duffing system and the wing rock phenomena to illustrate the effectiveness of the proposed control scheme.

Real Time Control for the Position and Velocity of Robot Manipulator With Parameter Uncertainties (不確實性을 고려한 로보트 매니퓰레이터의 位置 및 速度에 대한 實時間 制御)

  • Lee, Gang-Du;Kim, Gyeong-Nyeon;Han, Seong-Hyeon;Lee, Jin;Lee, Jong-Nyeon;Kim, Hwi-Dong
    • Journal of Ocean Engineering and Technology
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    • v.9 no.2
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    • pp.30-40
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    • 1995
  • In this paper, it is proposed a robust control scheme for real time control of a robot manipulator with parameter uncertainties. The focus of this paper is a new approach of multivariable control schemes for an assembly robot manipulator to achieve the accurate trajectory tracking by joint angles. The proposed control scheme consists of a multivariable feedforward controller and feedback controller. In this control scheme, the feedback controller consists of proportional-derivative type and is designed by the pole placement method. The feedforward controller uses the inverse of the linealized model of robot manipulator dynamics. This feedback controller ensures that each joint enables to track any reference trajectory. The proposed robot controller scheme has a computational efficiency.

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Adaptive Fuzzy Sliding Mode Control for Uncertain Nonlinear Systems

  • Seo, Sam-Jun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.1
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    • pp.12-18
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    • 2011
  • This paper deals with a new adaptive fuzzy sliding mode controller and its application to an inverted pendulum. We propose a new method of adaptive fuzzy sliding mode control scheme that the fuzzy logic system is used to approximate the unknown system functions in designing the SMC of uncertain nonlinear systems. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. Sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved.