Computation of weighted moments of discrete-time systems using experimental data

For an unknown linear discrete-time system, a simple algorithm for computing the weighted moments of the system from experimental input-output data is derived. When the measured output is contaminated with noise and/or if a system has a long tail of impulse response, it is difficult to exactly obtai...

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Bibliographic Details
Published in2017 17th International Conference on Control, Automation and Systems (ICCAS) pp. 1191 - 1195
Main Authors Jiho Hwang, Hyohee Lee, Seungpyo Cha, Young Chol Kim
Format Conference Proceeding
LanguageEnglish
Published Institute of Control, Robotics and Systems - ICROS 01.10.2017
Subjects
Computational modeling
Discrete-time systems
method of moment matching
Method of moments
moments of discrete-time system
Noise measurement
Parameter estimation
Pollution measurement
Signal to noise ratio
time-weighted moment
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Summary:For an unknown linear discrete-time system, a simple algorithm for computing the weighted moments of the system from experimental input-output data is derived. When the measured output is contaminated with noise and/or if a system has a long tail of impulse response, it is difficult to exactly obtain the time moments of output signals. To overcome this drawback, we suggest first introducing a digital filter to the measured output and then obtaining the weighted moments for both input and filtered output data. Subsequently the weighted moments of the discrete-time system are algebraically computed using both the input and output weighted moments. The proposed algorithm is applied to the identification of the parameters of a discrete-time low-order model from a rectangular pulse response with a random noise.
DOI:10.23919/ICCAS.2017.8204408