Sliding-window neural state estimation in a power plant heater line
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Publication:2783656
DOI10.1002/acs.657zbMath0991.93552OpenAlexW1989026782MaRDI QIDQ2783656
R. Zoppoli, Angelo Alessandri, Thomas Parisini
Publication date: 8 September 2002
Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/acs.657
Neural networks for/in biological studies, artificial life and related topics (92B20) Application models in control theory (93C95)
Cites Work
- An innovation representation for nonlinear systems with application to parameter and state estimation
- On global univalence theorems
- A receding-horizon regulator for nonlinear systems and a neural approximation
- Nonlinear stabilization by receding-horizon neural regulators
- Neural networks for nonlinear state estimation
- Neural approximators for nonlinear finite-memory state estimation
- On exact filters for continuous signals with discrete observations
- Stochastic stability of the discrete-time extended Kalman filter
- A neural state estimator with bounded errors for nonlinear systems
- Observer design for nonlinear systems with discrete-time measurements
- Moving horizon observers and observer-based control
- Neural approximations for multistage optimal control of nonlinear stochastic systems
- Nonlinear receding-horizon state estimation by real-time optimization technique
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