Cargando…
Event-triggered state estimator design for unknown input and noise-correlated random system
In this study, an event-driven state estimator is designed for stochastic systems that contain unknown inputs and processes as well as correlated measurement noise. First, the event-triggered state estimator's gain is deduced by using the random stability theory and Lyapunov's function. Th...
Autores principales: | He, Liu, Zhao, Yingjun, Dong, Qingkuan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7232098/ https://www.ncbi.nlm.nih.gov/pubmed/32435709 http://dx.doi.org/10.1016/j.heliyon.2020.e03832 |
Ejemplares similares
-
Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input
por: Zhou, Jie, et al.
Publicado: (2016) -
Full observability and estimation of unknown inputs, states and parameters of nonlinear biological models
por: Villaverde, Alejandro F., et al.
Publicado: (2019) -
EM and SAGE Algorithms for DOA Estimation in the Presence of Unknown Uniform Noise
por: Gong, Ming-Yan, et al.
Publicado: (2023) -
The Role of Input Noise in Transcriptional Regulation
por: Tkačik, Gašper, et al.
Publicado: (2008) -
Adaptive stochastic resonance for unknown and variable input signals
por: Krauss, Patrick, et al.
Publicado: (2017)