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Identification of dual-rate sampled output-error systems with unknown time-delays and orders

Kongzhi yu Juece/Control and Decision 2024年第9期39卷 3006-3012页

作者： Jiao F. Cao Y.-Q. Xie L. School of Internet of Things Engineering Jiangnan University Wuxi 214122 China Wuxi Advance Technologies Inc. Wuxi 214161 China

An orthogonal matching pursuit iterative identification algorithm is proposed for dual-rate sampled output-error systems with unknown time-delays and orders based on finite number of sampled data. Firstly, the identification model of the target system is established based on the dual-rate sampled data. Secondly, considering the input time-delay and the system order are both unknown, by means of the overparameterization method and taking the regression items of the noise-free output data and that of the input data as sufficient length, a sparse system is derived and its sparsity is the number of parameters to be identified. Furthermore, the idea of auxiliary model and the sparse recovery method in compressed sensing are combined for interactive estimation of the parameter vector and the noise-free outputs, where the parameter vector is estimated by using the orthogonal matching pursuit algorithm, the auxiliary model is constructed based on which and then the noise-free outputs are calculated accordingly and applied in turn for updating the parameter vector. Finally, the system order and the input time-delay are calculated according to the structure of the obtained parameter vector. The simulation experiments verify that the proposed algorithm can provide accurate joint estimation of system parameters, time-delay and order based on small amounts of sampled data. © 2024 Northeast University. All rights reserved.

关键词： auxiliary model dual-rate sampled system order estimation orthogonal matching pursuit parameter identification time-delay estimation

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hλ-order Analysis for Linear Time-Varying Systems

hλ-Order Analysis for Linear Time-Varying Systems

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第二十九届中国控制会议

作者： MA Hongbin,WANG Meiling School of Automation,Beijing Institute of Technology

A technique of order estimate,calledλ-order analysis,is developed in this *** technique can usually provide delicate order estimates for dynamical systems especially for linear time-varying *** notations of λ[·] and h[·] are introduced to capture the growth of *** of λ[·] and h[·] are discussed in details and examples of using this technique are illustrated to demonstrate its usage and easiness in analyzing stability of linear time-varying systems.

关键词： order estimation λ-order Analysis Linear Time-varying Systems Discrete-time Systems

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Identification of FIR Systems with Quantized Input and Binary-Valued Observations Under A Priori Parameter Constraint

Identification of FIR Systems with Quantized Input and Binar...

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第三十九届中国控制会议

作者： Tian Yuan Quanjun Liu Jin Guo School of Automation and Electrical Engineering University of Science and Technology Beijing Science and Technology on Space Physics Laboratory Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education

This paper investigates the identification of FIR（finite impulse response） systems with quantized input and binaryvalued observations. First, we obtain the ML（maximum likelihood） function of the available data, and construct an estimation algorithm of the unknown parameters when solving the maximum likelihood solution by transforming it into the solution to a set of linear equations. Secondly, based on the weighted least squares optimization technique, we establish the corresponding estimation algorithms in the case that the unknown parameters respectively satisfy a priori equality constraint and inequality constraint. Then, the AIC criterion is designed for estimating the order of the system. Finally, a numerical simulation example is employed to verify the effectiveness of the theoretical results obtained.

关键词： FIR systems Binary-valued Observations Parameter Constraint order estimation

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