Event-based state and fault estimation for stochastic nonlinear system with Markov packet dropout. (English) Zbl 1481.93129
Summary: This paper investigates the event-based state and fault estimation problem for stochastic nonlinear system with Markov packet dropout. By introducing the fictitious noise, the fault is augmented to the system state. Then combining the unscented Kalman filter (UKF) with event-triggered and Markov packet dropout, the modified UKF is proposed to estimate the state and fault. Meanwhile, the stochastic stability of the proposed filter is also discussed. Finally, two simulation results illustrate the performance of the proposed method.
MSC:
| 93E10 | Estimation and detection in stochastic control theory |
| 93E11 | Filtering in stochastic control theory |
| 93E15 | Stochastic stability in control theory |
| 93C65 | Discrete event control/observation systems |
| 93C10 | Nonlinear systems in control theory |
Keywords:
stochastic nonlinear system; event-based state and fault estimation; unscented Kalman filter; stochastic stabilityReferences:
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