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A Delta Operator State Estimation Algorithm for Discrete-Time Systems With State Time-Delay
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DOI：10.1109/LSP.2024.3519897.png)
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Abstract
En 中文
This letter presents a state estimation algorithm for linear discrete-time systems with state-delay. In order to overcome the difficulty that the traditional Kalman filter cannot estimate the states of the systems with state-delay, a state estimation strategy is developed by combining the auxiliary model with the delta operator. Then, by constructing and minimizing the covariance matrix of the state reconstruction errors, a delta operator state estimation algorithm is derived and it can fulfill effective state estimation for the linear discrete-time system with state-delay. Moreover, the convergence proof is provided by means of stochastic stability theory. Finally, the experimental results demonstrate that the developed state estimation method is effective.
Keywords:
State estimation
Vectors
Signal processing algorithms
Mathematical models
Delays
Covariance matrices
Convergence
Stochastic processes
Nonlinear systems
Kalman filters
Kalmam filtering
state-delay
state estimation
signal processing
Journal
IF:
9.6
Papers:
1.1W
Citations:
1.7W
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