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

Science China(Information Sciences) 2020年第1期63卷 140-151页

作者： Jin GUO Jing-Dong DIAO School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education

This paper addresses the identification of finite impulse response(FIR) systems with both quantized and event-triggered observations. An event-triggered communication scheme for the binary-valued output quantization is introduced to save communication resources. Combining the empirical-measure-based identification technique and the weighted least-squares optimization, an algorithm is proposed to estimate the unknown parameter by full use of the received data and the not-triggered condition. Under quantized inputs, it is shown that the estimate can strongly converge to the real values and the estimator is asymptotically efficient in terms of the Cram′er-Rao lower bound. Further, the limit of the average communication rate is derived and the tradeoff between this limit and the estimation performance is discussed. Moreover, the case of multi-threshold quantized observations is considered. Numerical examples are included to illustrate the obtained main results.

关键词： identification FIR systems prediction-based event-triggered communication quantized observations convergence performance

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Analysis of quantization noise and state estimation with quantized measurements

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控制理论与应用（英文版） 2011年第1期9卷 66-75页

作者： Xu, Jian Li, Jianxun Xu, Sheng Department of Automation Shanghai Jiao Tong University Shanghai 200240 China College of Mechanical Engineering Chongqing University Chongqing 400030 China

The approximate correction of the additive white noise model in quantized Kalman filter is investigated under certain conditions. The probability density function of the error of quantized measurements is analyzed theoretically and experimentally. The analysis is based on the probability theory and nonparametric density estimation technique, respectively. The approximator of probability density function of quantized measurement noise is given. The numerical results of nonparametric density estimation algorithm demonstrate that the theoretical conclusion is reasonable. Based on the analysis of quantization noise, a novel algorithm for state estimation with quantized measurements also is proposed. The algorithm is based on the least-squares estimator and unscented transform. By least-squares estimator, the effective information is extracted from the quantized measurements. Also, using the information to update the estimated state can give a better estimation under the influence of quantization. The root mean square error (RMSE) of the proposed algorithm is compared with the RMSE of the existing methods for a typical tracking scenario in wireless sensor networks systems. Simulations provide a strong evidence that this tracking algorithm could indeed give us a more precise estimated result.

关键词： Wireless sensor networks quantized observations Nonparametric density estimation Least-squares method Unscented transform

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State Estimation with quantized Measurements in Wireless Sensor Networks

State Estimation with Quantized Measurements in Wireless Sen...

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第二十九届中国控制会议

作者： XU Jian,LI Jianxun Department of Automation,Shanghai Jiao Tong University,Shanghai,200240,P.R.China

The problem of state estimation with quantized measurements is *** to the nonlinearity of the quantizer,estimating the system state is a nonlinear and non-Gaussian estimation problem even if the system is linear and Gaussian.A novel algorithm for approximate minimum mean square error（MMSE）state estimation with quantized measurement is *** algorithm is based on careful analysis for the quantized *** effective information extraction from the quanti-tative measurement,the true measurement value is reestablished *** evaluation and comparison of the proposed algorithm with the existing methods by simulation of a typical tracking scenario in Wireless Sensor Networks（WSN） systems are *** numerical results show that the tracking algorithm is effective.

关键词： Wireless Sensor Networks quantized observations Minimum Mean Squared Error(MMSE) Unscented Trans-form Decentralized State Estimation

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