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robust identification for multi_section freeway traffic models

控制理论与应用（英文版） 2005年第3期3卷 213-217页

作者： Zhongke SHI Institute of Air Traffic Management Northwestem Polytechnical University Xi＇an Shaanxi 710072 China

Since it is difficult to fit measured parameters using the conventional traffic model, a new traffic density and average speed model is introduced in this paper. To determine traffic model structures accurately, a model identification method for uncertain nonlinear system is developed. To simplify uncertain nonlinear problem, this paper presents a new robust criterion to identify the multi-section traffic model structure of freeway efficiently. In the new model identification criterion, numerically efficient U-D factofization is used to avoid computing the determinant values of two complex matrices. By estimating the values of U-D factor of data matrix, both the upper and lower bounds of system uncertainties are described. Thus a model structure identification algorithm is proposed. Comparisons between identification outputs and simulation outputs of traffic states show that the traffic states can be accurately predicted by means of the new traffic models and the structure identification criterion.

关键词： Traffic model robust identification Traffic prediction

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Study on an Adaptive Algorithm for Time-varying System

Study on an Adaptive Algorithm for Time-varying System

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第36届中国控制会议

作者： KIM KwangHo GENG Yanfeng Yue Yaobin College of Information & Control Engineering China University of Petroleum(East China) Automation Engineering Faculty Kimchaek University of TechnologyCAS College of Automation & Electronic Engineering Qingdao University of Science & Technology

ISBN: (纸本)9781538629185

In this paper,we presented the derivation of an adaptive algorithm for time-varying system and verified that it satisfied convergence properties.Based on the concept of distance in parameter space,we proposed a robust identification method which identified the smallest set of discrete transfer functions under the assumption that its parameters were time-varying and described derivation of an adaptive law based on verification and update algorithm of the identified model set.We also described that the proposed algorithm satisfied the convergence properties through numerical simulation.

关键词： adaptive algorithm time-varying system parameter estimation robust identification

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identification of Linear Systems with both Bias and Variance Disturbances

Identification of Linear Systems with both Bias and Variance...

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1994年中国控制会议

作者： Chen WEI and Lei GUO Institute of Systems Science, Chinese Academy of Science. Beijing, 100080, China

＜正＞identification/approximation problems for discrete-time linear systems with both bias and variance disturbances are addressed in the paper. The identification algorithms only depend on the time-domain input-output measurements. Strong consistency as well as estimation/approximation error bounds are established in terms of L∞-norm, in particular, it is shown that the bias disturbance does not upset the L∞-strong consistency of the identification algorithms.

关键词： robust identification least-squares model reduction stochastic process strong consistency.

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