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Parameter estimation for a multivariable state space system with d-step state-delay
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DOI：10.1016/j.jfranklin.2013.01.004.png)
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Abstract
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This paper considers the identification problem of the state space model with d-step state-delay for multivariable systems and presents a state estimation based recursive least squares parameter identification algorithm by using the hierarchical identification principle. Combining the linear transformation and the property of the shift operator, a state space system is transformed into an equivalent canonical state space model and its identification model and the corresponding identification algorithm are derived. Finally, an example is provided to validate the proposed theorems. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Keywords:
HIERARCHICAL IDENTIFICATION PRINCIPLE
NONUNIFORMLY SAMPLED SYSTEMS
LEAST-SQUARES ESTIMATION
MOVING AVERAGE SYSTEMS
ESTIMATION ALGORITHM
ITERATIVE ESTIMATION
MODEL
Journal
J
IF:
3.7
Papers:
6.3K
Citations:
1.5W