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System identification in a networked environment using second order statistical properties
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DOI：10.1016/j.automatica.2012.11.039.png)
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System identification for networked control is considered. Due to the time-delays in the network, it can be difficult to work with a discrete-time model and a continuous-time model is therefore chosen. A covariance function based method that relies on the second order statistical properties of the output signal, where it is assumed that the input signal samples are from a discrete-time white noise sequence, is proposed for estimating the parameters. The method is easy to use since the actual time instants when new input signal levels are applied at the actuator do not have to be known. An analysis of the networked system and the effects of the time-delays is made, and the results of the analysis motivate and support the chosen approach. Numerical studies indicate that the method is robust to randomly distributed time-delays, packet drop-outs, and additive measurement noise. (C) 2012 Elsevier Ltd. All rights reserved.
Keyword:
Networked control systems
Continuous-time model
System identification
Parameter estimation
Covariance function
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IF:
5.9
论文数:
1.2W
被引数:
5.2W
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