Machine-learning-based state estimation and predictive control of nonlinear processes
Sign Up to like & getrecommendations! Published in 2021 at "Chemical Engineering Research and Design"
DOI: 10.1016/j.cherd.2021.01.009
Abstract: Abstract Machine learning techniques have demonstrated their capability in capturing dynamic behavior of complex, nonlinear chemical processes from operational data. As full state measurements may be unavailable in chemical plants, this work proposes two machine-learning-based… read more here.
Keywords: learning based; based state; state estimation; state ... See more keywords
Set-Based State Estimation: A Polytopic Approach
Sign Up to like & getrecommendations! Published in 2020 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2020.12.367
Abstract: Abstract This paper is concerned with guaranteed parameter estimation for discrete-time nonlinear systems subject to bounded uncertainties. The proposed approach is based on polytopic set parameterizations. Similar to other estimation and filtering approaches, the presented… read more here.
Keywords: set based; based state; approach; state estimation ... See more keywords
Dissipativity-based state estimation of delayed static neural networks
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.03.059
Abstract: This paper proposes a dissipativity-based state estimation methodology for static neural networks with time-varying delay. An Arcak-type observer is used to construct the estimation error system. To reduce the conservatism of observer design, a LyapunovKrasovskii… read more here.
Keywords: methodology; based state; estimation; static neural ... See more keywords
Pseudo-Dynamic Network Modeling for PMU-Based State Estimation of Hybrid AC/DC Grids
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2017.2777185
Abstract: This paper presents a PMU-based state estimation (SE) algorithm that uses a pseudo-dynamic network modeling approach. The pseudo-dynamic network model combines different equations with static network equations. Then it applies the weighted least squares algorithm… read more here.
Keywords: state; based state; pmu based; dynamic network ... See more keywords
Kernel-Based State-Space Kriging for Predictive Control
Sign Up to like & getrecommendations! Published in 2023 at "IEEE/CAA Journal of Automatica Sinica"
DOI: 10.1109/jas.2023.123459
Abstract: In this paper, we extend the state-space kriging (SSK) modeling technique presented in a previous work by the authors in order to consider non-autonomous systems. SSK is a data-driven method that computes predictions as linear… read more here.
Keywords: state space; kernel based; space kriging; based state ... See more keywords
Event-Based State Estimation Under the Presence of Multiplicative Measurement Noise
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2019.2915403
Abstract: An event-based state estimation problem for a discrete-time system when the measurements are corrupted with multiplicative noise is considered in this letter. A general event-based sampling is employed to obtain the measurements, where the event-based… read more here.
Keywords: event based; based state; state estimation; noise ... See more keywords
Relaxed Observer-Based State Estimation of Discrete-Time Takagi–Sugeno Fuzzy Systems Based on an Augmented Matrix Approach
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Fuzzy Systems"
DOI: 10.1109/tfuzz.2021.3129854
Abstract: In this paper, relaxed observer-based state estimation of discrete-time Takagi–Sugeno fuzzy systems is proposed via developing a new augmented matrix approach. In contrast with the recent method reported in the literature, a more advanced introduction… read more here.
Keywords: relaxed observer; estimation discrete; observer based; state estimation ... See more keywords