Neural-network-based output-feedback control with stochastic communication protocols
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Publication:2280768
DOI10.1016/j.automatica.2019.04.025zbMath1429.93112OpenAlexW2945686539WikidataQ127851426 ScholiaQ127851426MaRDI QIDQ2280768
Zidong Wang, Qing-Long Han, Derui Ding
Publication date: 19 December 2019
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.automatica.2019.04.025
output-feedback controladaptive dynamic programmingstochastic communication protocolsactor-critic structures
Feedback control (93B52) Nonlinear systems in control theory (93C10) Dynamic programming (90C39) Stochastic systems in control theory (general) (93E03)
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Cites Work
- Stochastic model predictive control for constrained discrete-time Markovian switching systems
- Filtering for a class of nonlinear discrete-time stochastic systems with state delays
- Observer-based \(\mathcal{H}_\infty\) control of networked systems with stochastic communication protocol: the finite-horizon case
- Online actor-critic algorithm to solve the continuous-time infinite horizon optimal control problem
- Adaptive fuzzy logic control of discrete-time dynamical systems
- Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming
- Adaptive NN control for a class of discrete-time non-linear systems
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