Abstract
To overcome the influence from deterministic type load disturbance with unknown dynamics, a biaseliminated subspace identification method is proposed for consistent estimation. By decomposing the output response into three parts, deterministic, disturbed and stochastic components, in terms of the linear superposition principle, an LQ decomposition approach is developed to eliminate the disturbance and noise effect for unbiased estimation of the deterministic system state. Subsequently, a shift-invariant approach is given to retrieve the state matrices. Consistent estimation on the state matrices is analyzed with a proof. Illustrative example of open-loop system identification is shown to demonstrate the effectiveness and merit of the proposed method.
Original language | English |
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Pages (from-to) | 243-251 |
Number of pages | 9 |
Journal | Systems Science and Control Engineering |
Volume | 5 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jun 2017 |
Keywords
- Consistent estimation
- Kalman innovation form
- Load disturbance
- LQ decomposition
- Subspace identification
ASJC Scopus subject areas
- Control and Systems Engineering
- Control and Optimization
- Artificial Intelligence