• Title/Summary/Keyword: stochastic control systems

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Serviceability-oriented analytical design of isolated liquid damper for the wind-induced vibration control of high-rise buildings

  • Zhipeng Zhao;Xiuyan Hu;Cong Liao;Na Hong;Yuanchen Tang
    • Smart Structures and Systems
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    • v.33 no.1
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    • pp.27-39
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    • 2024
  • The effectiveness of conventional tuned liquid dampers (TLDs) in controlling the wind-induced response of tall flexible structures has been indicated. However, the impaired control effect in the detuning condition or a considerably high mass cost of liquid may be incurred in ensuring the high-level serviceability. To provide an efficient TLD-based solution for wind-induced vibration control, this study proposes a serviceability-oriented optimal design method for isolated TLDs (ILDs) and derives analytical design formulae. The ILD is implemented by mounting the TLD on the linear isolators. Stochastic response analysis is performed for the ILD-equipped structure subjected to stochastic wind and white noise, and the results are considered to derive the closed-form responses. Correspondingly, an extensive parametric analysis is conducted to clarify a serviceability-oriented optimal design framework by incorporating the comfort demand. The obtained results show that the high-level serviceability demand can be satisfied by the ILD based on the proposed optimal design framework. Analytical design formulae can be preliminarily adopted to ensure the target serviceability demand while enhancing the structural displacement performance to increase the safety level. Compared with conventional TLD systems, the ILD exhibits higher effectiveness and a larger frequency bandwidth for wind-induced vibration control at a small mass ratio.

An Intelligent PID Controller based on Dynamic Bayesian Networks for Traffic Control of TCP (TCP의 트래픽 제어를 위한 동적 베이시안 네트워크 기반 지능형 PID 제어기)

  • Cho, Hyun-Choel;Lee, Young-Jin;Lee, Jin-Woo;Lee, Kwon-Soon
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.4
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    • pp.286-295
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    • 2007
  • This paper presents an intelligent PID control for stochastic systems with nonstationary nature. We optimally determine parameters of a PID controller through learning algorithm and propose an online PID control to compensate system errors possibly occurred in realtime implementations. A dynamic Bayesian network (DBN) model for system errors is additionally explored for making decision about whether an online control is carried out or not in practice. We apply our control approach to traffic control of Transmission Control Protocol (TCP) networks and demonstrate its superior performance comparing to a fixed PID from computer simulations.

An IMM Algorithm for Tracking Maneuvering Vehicles in an Adaptive Cruise Control Environment

  • Kim, Yong-Shik;Hong, Keum-Shik
    • International Journal of Control, Automation, and Systems
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    • v.2 no.3
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    • pp.310-318
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    • 2004
  • In this paper, an unscented Kalman filter (UKF) for curvilinear motions in an interacting multiple model (IMM) algorithm to track a maneuvering vehicle on a road is investigated. Driving patterns of vehicles on a road are modeled as stochastic hybrid systems. In order to track the maneuvering vehicles, two kinematic models are derived: A constant velocity model for linear motions and a constant-speed turn model for curvilinear motions. For the constant-speed turn model, an UKF is used because of the drawbacks of the extended Kalman filter in nonlinear systems. The suggested algorithm reduces the root mean squares error for linear motions and rapidly detects possible turning motions.

Performance analyses of RHLQG/FIRF controller

  • Yoo, Kyung-Sang;Kwon, Oh-Kyu
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.88-94
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    • 1993
  • In this paper we analyze the RHLQG/FIRF optimal.contol law presented in [4,5] in order to stabilizes a stochastic linear time varying systems with modeling uncertainty. It is shown by the frequency domain analysis that the RHC is robuster than the LQ control law. Explicit LTR procedures are given to improve the robust performance of RHLQC/FIRF cotrol law. Using the mismatching function technique [8], we propose an LTR method which makes the RHLQG/FIRF controller recover the feedback properties of the R.HC law. Also we compare the LTR performance of the RHLQC/FIRF via simulation with conventional LTR methods.

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Stability Analysis of Networked Control Systems with Packet Dropouts (패킷 손실을 고려한 네트워크 제어 시스템의 안정성 분석)

  • Kim, Jae-Man;Park, Jin-Bae;Choi, Yoon-Ho
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.1731_1732
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    • 2009
  • This paper presents a stability analysis of networked control systems with packet dropouts. The packet dropouts are modeled as a linear function of the stochastic variable satisfying Bernoulli random binary distribution and weighted moving average (WMA). The observer based controller scheme is designed to exponentially mean square stabilize the NCS. Simulation results is provided to show the applicability of the proposed method.

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The Nonlinear State Estimation of the Aircraft using the Adaptive Extended Kalman Filter (적응형 확장 칼만 필터를 이용한 항공기의 비선형 상태추정)

  • Jong Chul Kim;Sang Jong Lee;Anatol A. Tunik
    • Journal of Institute of Control, Robotics and Systems
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    • v.5 no.2
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    • pp.158-165
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    • 1999
  • 비행시험을 통해 획득한 데이터의 해석과정에서 대상 항공기의 크기가 소형인 경우에는 엔진진동이나 외부의 교란에 의한 잡음이나 바이어스 등의 강도가 높기 때문에 데이터의 처리과정에서 많은 문제점을 산출하게 된다. 이와 같은 문제점을 해결하기 위해 상태추정 알고리즘이 사용되며, 본 논문에서는 항공기의 비선형 세로운동 방정식의 경우에 확장형 칼만 필터를 적용하여 항공기 세로운동의 상태변수들을 추정하였으며, 또한 확률근사과정, 이노베이션에 대한 궤환 적응 등 적응형 칼만 필터를 사용하여 수렴속도와 정확도 둥을 향상시킨 알고리즘을 제안하고 그 결과를 나타내었다.

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Stochastic Design Approach for the Guidance and Control System of an Automatic Landing Vehicle

  • Minami, Yoshinori;Miyazawa, Yoshikazu;Shimada, Yuzo
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.41-46
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    • 1998
  • In this paper, a stochastic approach based on a Monte Carlo simulation method for the design of a guidance and control (G & C) system of an automatic landing flight experiment (ALFLEX) vehicle is presented. The aim of this study is to design a G & C system robust against uncertainties in the vehicular dynamics. In this study, uncertain parameters and disturbances are treated as random variables in the Monte Carlo simulation. Then, some controller gains in the G & C system are tuned to satisfy conditions concerning the states at touchdown. The proposed method was applied to the ALFLEX vehicle. The simulation results shored the effectiveness of the present approach.

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Nonlinear Stochastic Stability for Steam Generator Water Level Control System (증기발생기 수위제어의 확률론적 안정성)

  • Park, You-Cho;Chung, Chang-Hyun;Oh, Je-Kyun
    • Nuclear Engineering and Technology
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    • v.27 no.2
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    • pp.155-164
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    • 1995
  • The steam generator water level control system is studied as a class of randomly sampled nonlinear control systems. The sampling interval and the loop amplification factor are considered as random variables in order to take the operator behavior in account. Stochastic stability using Lyapunov method is used without determining such Lyapunov function. The derived stability criterion is verified with time-domain simulation using the data of CANDU type nuclear power plant, Wolsung 1.

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Dynamic and Stochastic Modeling of Litten´s space Inertial Reference Unit(SIRU)

  • Park, H.T.;K.Y Yong;B.S. Suk
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.167.4-167
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    • 2001
  • Accurate mathematical models of spacecraft components are an essential of spacecraft attitude control system design, analysis and simulation. Gyro is one of the most important spacecraft components used for attitude propagation and control. Gyro errors may seriously degrade the accuracy of the calculated spacecraft angular rate and of attitude estimates due to inherent drift and bias errors. In this paper, a detailed mathematical model of gyro containing the relationships for predicting spacecraft angular rate and disturbances is proposed. Stochastic model describing random drift behavior is discussed in frequency domain and time domain. In order to illustrate this approach, we analyze the behavior for Litton´s Space Inertial Reference Uint(SIRU).

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Recursive Optimal State and Input Observer for Discrete Time-Variant Systems

  • Park, Youngjin;J.L.Stein
    • Transactions on Control, Automation and Systems Engineering
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    • v.1 no.2
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    • pp.113-120
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    • 1999
  • One of the important challenges facing control engineers in developing automated machineryis to be able to monitor the machines using remote sensors. Observrs are often used to reconstruct the machine variables of interest. However, conventional observers are unalbe to observe the machine variables when the machine models, upon which the observers are based, have inputs that cannot be measured. Since this is often the case, the authors previsously developed a steady-state optimal state and input observer for time-invariant systems [1], this paper extends that work to time-variant systems. A recursive observer, similar to a Kalman-Bucy filter, is developed . This optimal observer minimizes the trace of the error variance for discrete , linear , time-variant, stochastic systems with unknown inputs.

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