Displaying similar documents to “A new estimation algorithm from measurements with multiple-step random delays and packet dropouts.”

Filtering of signals transmitted in multichannel from Chandrasekhar and Riccati recursions.

S. Nakamori, A. Hermoso, J. Jiménez, J. Linares (2005)

Extracta Mathematicae

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In this paper two recursive algorithms are proposed and compared as a solution of the least mean-squared error linear filtering problem of a wide-sense stationary scalar signal from uncertain observations perturbed by white and coloured additive noises. Considering that the state-space model of the signal is not available and that the variables modelling the uncertainty are not independent, the proposed algorithms are derived by using covariance information. The difference between both...

On-line parameter and delay estimation of continuous-time dynamic systems

Janusz Kozłowski, Zdzisław Kowalczuk (2015)

International Journal of Applied Mathematics and Computer Science

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The problem of on-line identification of non-stationary delay systems is considered. The dynamics of supervised industrial processes are usually modeled by ordinary differential equations. Discrete-time mechanizations of continuous-time process models are implemented with the use of dedicated finite-horizon integrating filters. Least-squares and instrumental variable procedures mechanized in recursive forms are applied for simultaneous identification of input delay and spectral parameters...

Quadratic estimation from non-independent uncertain observations with coloured noise.

S. Nakamori, R. Caballero, A. Hermoso, J. Jiménez, J. Linares (2004)

Extracta Mathematicae

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Recursive least-squares quadratic filtering and fixed-point smoothing algorithms for signal estimation from uncertain observations are derived when the uncertainty is modeled by not necessarily independent variables and the observations contain white plus coloured noise. The proposed estimators do not require the knowledge of the state-space of the model generating the signal, but only the moments, up to the fourth one, of the processes involved, along with the probability that the signal...

An instrumental variable method for robot identification based on time variable parameter estimation

Mathieu Brunot, Alexandre Janot, Peter Young, Francisco Carrillo (2018)

Kybernetika

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This paper considers the data-based identification of industrial robots using an instrumental variable method that uses off-line estimation of the joint velocities and acceleration signals based only on the measurement of the joint positions. The usual approach to this problem relies on a ‘tailor-made’ prefiltering procedure for estimating the derivatives that depends on good prior knowledge of the system's bandwidth. The paper describes an alternative Integrated Random Walk SMoothing...