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Subsystem model-based close-loop grey-box identification method for hydraulic stewart platform

Journal of Harbin Institute of Technology(New Series) 2011年第2期18卷 107-112页

作者：唐建林董彦良赵克定 School of Mechatronics Engineering Harbin Institute of Technology

In order to solve the problem of difficult modeling and identification caused by time-variable parameters,multiple inputs and outputs and unstable open loop,a subsystem model-based close-loop grey-box identification method was put forward when consider the main coupling effects of hydraulic Stewart ***,the whole system is divided into three TITO(Two Input Two Output) subsystems according to the characteristics of the pseudo-mass matrix,hence transfer function matrix model of the subsystem can also be ***,since the Stewart platform is unstable,the close-loop transfer model of the subsystem is derived under the proportional *** inverse M serial is adopted as the identification signal to get the experimental *** parameters of the subsystem are determined in close-loop indirect identification by PEM(prediction error method).Finally,a case study validates the correctness and effectiveness of the subsystem model-based close-loop grey-box identification method for hydraulic Stewart platform.

关键词： hydraulic Stewart platform pseudo-mass matrix prediction error method close-loop indirect identification grey-box model

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Convergence Analysis of Parameter Estimation in System Identification

Convergence Analysis of Parameter Estimation in System Ident...

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第25届中国控制与决策会议

作者： Yan Zhibin Chen Caiyun Natural Science Research Center Harbin Institute of Technology

ISBN: (纸本)9781467355339

For linear time-invariant system model, this paper analyzes the convergence of parameter estimations as the length of the input-output data tends to infinity through prediction error method. It is known that the sequence of the prediction errors, called criterion functions, converges uniformly in the parameter with probability one as the data length tends to infinity. Given an input-output data of fixed length, the parameter estimation is represented by a set in general, instead of by a single point, on which the criterion function takes its minimum. Thus a mathematical feature of the convergence problem of parameter estimation is in that we are needed, from the convergence of a sequence of functions, to infer the convergence of the sequence of their sets of minimizing arguments. The Hausdorff metric, as a rational due tool, is suggested to measure the distance between sets and then is used to discuss the convergence problem here. We show that, according to Hausdorff metric, the convergence of parameter estimation can not be guaranteed in general, and give some conditions to guarantee.

关键词： system identification parameter estimate prediction error method Hausdorff metric

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Correlation Analysis Based Direct Identification of a Quadrotor Generalized Attitude Model Using Outdoor Flight Data

Correlation Analysis Based Direct Identification of a Quadro...

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第40届中国控制会议

作者： Jin-Cang Liu Li-Hui Geng Xiao-You Liu Yun-Wei Chang Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical EngineeringTianjin University of Technology and Education

This paper studies the direct identification of a quadrotor generalized attitude model（GAM） by utilizing the collected outdoor flight data corrupted with strong random wind disturbance. In order to diminish the ill effects caused by such disturbing winds on the identification accuracy, an improved correlation computation scheme is designed and then the prediction error method is applied to estimate the GAM and its associated noise model. Finally, model validations are given to demonstrate the effectiveness of the proposed identification procedure and the resulting estimated GAM.

关键词： Quadrotor Generalized attitude model Direct identification prediction error method Model validation

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Asymptotical Behavior of Parameter Estimation in prediction error Framework

Asymptotical Behavior of Parameter Estimation in Prediction ...

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第26届中国控制与决策会议

作者： Caiyun Chen Zhibin Yan Natural Science Research Center Harbin Institute of Technology

ISBN: (纸本)9781479937097

In prediction error method, it is known that the sequence of the criterion function converges uniformly in the parameter with probability one as the length of the input-output data tends to infinity. When the minimizing points of the limiting function criterion are not unique, the convergence of parameter estimation is not guaranteed in *** cases are distinguished. The case one is that the set of the minimizing points of the limiting function criterion is a continuum, and the case two is that the points of that set are isolated. Some interesting phenomena relating to the different cases are shown about the asymptotical behavior of parameter estimation through examples and theoretical analysis.

关键词： parameter estimation prediction error method Hausdorff metric system identification

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