Quantum mechanics

Algorithm

Control (management)

Engineering

Biology

Identification (biology)

Statistics

Feedback loop

Control engineering

Computer security

Computer science

Botany

Mathematical optimization

Covariance

Physics

Nonlinear system

Database

Mathematics

Unit circle

System identification

Loop (graph theory)

Artificial intelligence

Kalman filter

Geometry

Combinatorics

Closed loop

Subspace topology

Control theory (sociology)

Data modeling

State (computer science)

IFAC-PapersOnLine

This paper develops a closed-loop subspace identification algorithm for the systems with the stochastic part possessing zeros close to the unit circle. The proposed algorithm estimates the system under the feedback loop, taking the effect of the initial state into account. A nonlinear optimization technique is applied for computing the Kalman gain and the covariance of the innovation. Numerical simulation shows that the proposed algorithm successfully provides models by taking the initial effect.

Closed-loop subspace identification taking initial state into account