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Decomposition based least squares iterative estimation algorithm for two-input single-output output error systems
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DOI：10.1016/j.jfranklin.2014.10.001.png)
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This paper develops a decomposition based least squares iterative identification algorithm for two-input single-output (TISO) systems. The basic idea is to decompose a TISO system into two subsystems and then to identify each subsystem, respectively. Compared with the least squares based iterative algorithm, the proposed algorithm has less computational load. The simulation results indicate that the proposed algorithm is effective. (C) 2014 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Keyword:
MOVING AVERAGE SYSTEMS
MODEL-PREDICTIVE CONTROL
TIME NONLINEAR-SYSTEMS
PARAMETER-ESTIMATION
MULTIVARIABLE SYSTEMS
MATRIX EQUATIONS
COLORED NOISE
IDENTIFICATION
STATE
DELAYS
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3.7
论文数:
6.4K
被引数:
1.5W
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