Abstract
A time-weighted integral transform is presented to identify a continuous SISO or MIMO parametric model based on a single dynamic test under open-loop or closed-loop operation. Moving-horizon algorithms are proposed to obtain unbiased estimates of the model parameters. The off-line algorithm in a least-squares form and the on-line algorithm in a recursive form are provided. An effective technique based on pattern recognition is also developed to determine the system order and time delay from observed data in a simple manner. Furthermore, the proposed method can be easily applied as a model reduction technique that results in an ideal model with delay for any specified order.
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