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Identification of Wiener systems with binary-valued output observations

Yanlong Zhao, Le Yi Wang, G. George Yin, Ji-Feng Zhang
2007 Automatica  
This work is concerned with identification of Wiener systems whose outputs are measured by binary-valued sensors.  ...  The concept of joint identifiability of the core problem is introduced to capture the essential conditions under which the Wiener system can be identified with binary-valued observations.  ...  Acknowledgements The research of Yanlong Zhao and Ji-Feng Zhang was supported by the National Natural Science  ... 
doi:10.1016/j.automatica.2007.03.006 fatcat:dmaysnp4t5dxvhzqbccniwsduu

Real-Time Parameter Estimation of PMDC Motors Using Quantized Sensors

Mohammad A. Obeidat, Le Yi Wang, Feng Lin
2013 IEEE Transactions on Vehicular Technology  
Index Terms-PMDC motors, parameter estimation, quantized observations, system identification. LaJ − s+ Ra La J km LaJ k b LaJ s+ µ J La Mohammad A.  ...  Quantized sensors are less expensive and remote controlled motors mandate signal quantization. Such limitations on observations introduce challenging issues in motor parameter estimation.  ...  CONCLUDING REMARKS This paper introduces a new method of identifying the model parameters, using binary-valued or quantized output observations.  ... 
doi:10.1109/tvt.2013.2251431 fatcat:s5nhpkgccndrrbip2d46xsghwy

Prediction-based event-triggered identification of quantized input FIR systems with quantized output observations

Jin Guo, Jing-Dong Diao
2019 Science China Information Sciences  
Prediction-based event-triggered identification of quantized input FIR systems with quantized output observations.  ...  Identification of Wiener systems with quantized observations was studied in [19, 20] . Ref. [21] addressed the problem of set membership system identification with quantized measurements.  ...  Acknowledgements This work was supported by National Natural Science Foundation of China (Grant No. 61773054). Guo J, et al. Sci China Inf Sci January 2020 Vol. 63 112201:12  ... 
doi:10.1007/s11432-018-9845-6 fatcat:rdrgmj2cmnakpnj2g5zfdtfeeu

Fixed-order FIR approximation of linear systems from quantized input and output data

V. Cerone, D. Piga, D. Regruto
2013 Systems & control letters (Print)  
all possible values of the input and output data consistent with their quantized measurements.  ...  The problem of identifying a fixed-order FIR approximation of linear systems with unknown structure, assuming that both input and output measurements are subjected to quantization, is dealt with in this  ...  Introduction In many engineering applications, only binary-valued or quantized measurement data Identification of dynamical systems from binary and quantized observations has attracted the attention of  ... 
doi:10.1016/j.sysconle.2013.09.012 fatcat:qw7cmi6jtrds5ojgn3ralh5sre

A compensation method for the packet loss deviation in system identification with event-triggered binary-valued observations

Jing-Dong Diao, Jin Guo, Changyin Sun
2020 Science China Information Sciences  
A compensation method for the packet loss deviation in system identification with event-triggered binary-valued observations. Sci China Inf Sci, 2020, 63(12): 229204, https://doi.  ...  Acknowledgements This work was supported by National Natural Science Foundation of China (Grant Nos. 61773054, 61520106009, U1713209). Supporting information Appendixes  ...  [2] used the maximum likelihood method to study identification of ARMA systems based on finitely quantized output observations with packet dropouts.  ... 
doi:10.1007/s11432-019-9802-0 fatcat:r43la5pjnzfb7c42l56pck5hpq

Identification of Hammerstein Systems with Quantized Observations [chapter]

Le Yi Wang, G. George Yin, Ji-Feng Zhang, Yanlong Zhao
2010 System Identification with Quantized Observations  
This work is concerned with identification of Hammerstein systems whose outputs are measured by quantized sensors.  ...  The concept of strongly scaled full rank signals is introduced to capture the essential conditions under which the Hammerstein system can be identified with set-valued observations.  ...  The work on nonlinear systems with binary-valued observations started with Wiener systems in [26] .  ... 
doi:10.1007/978-0-8176-4956-2_12 fatcat:xaij3zxnvrgodlnk3yslpbn4iy

Identification of Hammerstein Systems with Quantized Observations

Yanlong Zhao, Ji-Feng Zhang, Le Yi Wang, G. George Yin
2010 SIAM Journal of Control and Optimization  
This work is concerned with identification of Hammerstein systems whose outputs are measured by quantized sensors.  ...  The concept of strongly scaled full rank signals is introduced to capture the essential conditions under which the Hammerstein system can be identified with set-valued observations.  ...  The work on nonlinear systems with binary-valued observations started with Wiener systems in [26] .  ... 
doi:10.1137/070707877 fatcat:5uhyyiu34bgznp5lcnwldz5oia

Identification of the gain system with quantized observations and bounded persistent excitations

Jin Guo, YanLong Zhao
2013 Science China Information Sciences  
System identification with quantized observations and persistent excitations is a fundamental and difficult problem.  ...  As the first step, this paper takes the gain system for example to investigate the identification with quantized observations and bounded persistently exciting inputs.  ...  Acknowledgements The work was supported by National Natural Science Foundation of China (Grant No. 61174042), and Youth Innovation Promotion Association of Chinese Academy of Sciences (Grant No. 4106960  ... 
doi:10.1007/s11432-012-4761-x fatcat:ltrpc472rbhxha72cdbmte5c6e

A Weighted Least-Squares Approach to Parameter Estimation Problems Based on Binary Measurements

E. Colinet, J. Juillard
2010 IEEE Transactions on Automatic Control  
of the presence of measurement noise at the quantizer's input.  ...  This approach is based on the use of original weighted least-squares criteria: as opposed to other existing methods, it requires no dithering signal and it does not rely on an approximation of the quantizer  ...  [8] where the identification of infinite impulse response (IIR) systems and nonlinear Wiener systems is addressed.  ... 
doi:10.1109/tac.2009.2033842 fatcat:5zdrjuynlbbgtdgy32ovs2dngy

A new kernel-based approach to system identification with quantized output data [article]

Giulio Bottegal, Håkan Hjalmarsson, Gianluigi Pillonetto
2017 arXiv   pre-print
In this paper we introduce a novel method for linear system identification with quantized output data.  ...  Numerical simulations show the effectiveness of the proposed scheme, as compared to the state-of-the-art kernel-based methods when these are employed in system identification with quantized data.  ...  Algorithm 3: System identification with quantized output measurements Input: {y t } N t=1 , {u t } N −1 t=0 Output: {ĝ t } m t=1 Initialization: Set an initial value ofη (0) Repeat until convergence: (  ... 
arXiv:1610.00470v2 fatcat:y5sevdvu5neaxfaztejoczlemy

System identification using binary sensors

Le Yi Wang, Ji-Feng Zhang, G.G. Yin
2003 IEEE Transactions on Automatic Control  
System identification is investigated for plants that are equipped with only binary-valued sensors.  ...  Optimal identification errors, time complexity, optimal input design, and impact of disturbances and unmodeled dynamics on identification accuracy and complexity are examined in both stochastic and deterministic  ...  CONCLUSION Identification with binary-valued sensors is of practical importance and theoretical interest.  ... 
doi:10.1109/tac.2003.819073 fatcat:coglbbyoxffxbpg37izdqmpdha

Pattern-Moving-Based Parameter Identification of Output Error Models with Multi-Threshold Quantized Observations

Xiangquan Li, Zhengguang Xu, Cheng Han, Ning Li
2022 CMES - Computer Modeling in Engineering & Sciences  
with multi-threshold quantized observations.  ...  A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output (SIMO) or SISO nonlinear systems, and a SISO linear output  ...  The parameter identification of Wiener system was also studied in terms of quantized inputs and binary outputs in [26] .  ... 
doi:10.32604/cmes.2022.017799 fatcat:ztw6ovumqrapnmommjd6diil6i

Quantized Identification With Dependent Noise and Fisher Information Ratio of Communication Channels

Le Yi Wang, G. George Yin
2010 IEEE Transactions on Automatic Control  
System identification is studied in which the system output is quantized, transmitted through a digital communication channel, and observed afterwards.  ...  The methods of identification input designs that link general system parameters to core identification problems are reviewed.  ...  For clarity, we will concentrate on the scalar observations first. That is, the sensor output is scalar and quantized with possible values .  ... 
doi:10.1109/tac.2009.2039242 fatcat:mrdbgrzet5ekhlcj5hytqdft4q

Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs

Jin Guo, Le Yi Wang, George Yin, Yanlong Zhao, Ji-Feng Zhang
2015 Automatica  
This paper introduces identification algorithms for finite impulse response systems under quantized output observations and general quantized inputs.  ...  Optimal input design is given. Also the joint identification of noise distribution functions and system parameters is investigated.  ...  Wang et al. (2003) gave a strong consistent identification algorithm with binary-valued observations.  ... 
doi:10.1016/j.automatica.2015.04.009 fatcat:hjnvn77wkbbstgspbd5nq4cvnm

Identification Input Design for Consistent Parameter Estimation of Linear Systems With Binary-Valued Output Observations

Le Yi Wang, G. George Yin, Yanlong Zhao, Ji-Feng Zhang
2008 IEEE Transactions on Automatic Control  
This paper presents conditions on input signals that characterize their probing richness for strongly consistent parameter estimation of linear systems with binary-valued output observations.  ...  The findings of this paper provide a foundation to study identification of systems that either use binary-valued or quantized sensors or involve communication channels, which mandate quantization of signals  ...  The algorithms are uniquely designed for binary-valued or quantized output observations with output disturbances.  ... 
doi:10.1109/tac.2008.920222 fatcat:2yjm5hkaynagbjelp45hdekcxe
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