Eventâtriggered robust state estimation for wireless sensor networks
Sign Up to like & getrecommendations! Published in 2019 at "Asian Journal of Control"
DOI: 10.1002/asjc.2051
Abstract: Robust state estimation problem subject to a communication constraint is investigated in this paper for a class of wireless sensor networks constituted by multiple remote sensor nodes and a fusion node. An analytical robust fusion… read more here.
Keywords: state estimation; sensor; wireless sensor; robust state ... See more keywords
Time-domain harmonic state estimation of nonlinear load power systems with under-determined condition based on the extended Kalman filter
Sign Up to like & getrecommendations! Published in 2017 at "International Transactions on Electrical Energy Systems"
DOI: 10.1002/etep.2242
Abstract: This contribution presents a time-domain methodology for harmonic state estimation of power systems with nonlinear loads based on the extended Kalman filter (EKF). The output variables measurements to be used in the state estimation algorithm… read more here.
Keywords: state; state estimation; time domain; power ... See more keywords
Delay-distribution-dependent non-fragile state estimation for discrete-time neural networks under event-triggered mechanism
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3516-z
Abstract: In this paper, the event-triggered non-fragile state estimation problem is considered for a class of uncertain discrete-time neural networks with random delays and state-dependent stochastic disturbances. The norm-bounded uncertainty goes into all the parameters of… read more here.
Keywords: state; non fragile; fragile state; state estimation ... See more keywords
Robust State Estimation for Delayed Complex-Valued Neural Networks
Sign Up to like & getrecommendations! Published in 2017 at "Neural Processing Letters"
DOI: 10.1007/s11063-017-9626-2
Abstract: This paper is concerned with the state estimation problem for the uncertain complex-valued neural networks with time delays. The parameter uncertainties are assumed to be norm-bounded. Through available output measurements containing nonlinear Lipschitz-like terms, we… read more here.
Keywords: state; valued neural; neural networks; state estimation ... See more keywords
State Estimation for Genetic Regulatory Networks with Two Delay Components by Using Second-Order Reciprocally Convex Approach
Sign Up to like & getrecommendations! Published in 2021 at "Neural Processing Letters"
DOI: 10.1007/s11063-021-10633-4
Abstract: This paper presents a state estimation for genetic regulatory networks with two delay components by using second-order reciprocally convex approach. The additive time delay plays an independence and the variation of the delay components with… read more here.
Keywords: state; delay components; second order; delay ... See more keywords
Asymptotic state estimation for linear systems with sensor and actuator faults
Sign Up to like & getrecommendations! Published in 2019 at "Science China Information Sciences"
DOI: 10.1007/s11432-018-9782-9
Abstract: This paper investigates the asymptotic state estimation problem for linear systems with sensor and actuator faults, where the faults are modeled via multiple modes. For the case of sensor faults, we first introduce a new… read more here.
Keywords: state; system; sensor actuator; state estimation ... See more keywords
An operating state estimation model for integrated energy systems based on distributed solution
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in energy"
DOI: 10.1007/s11708-020-0687-y
Abstract: In view of the disadvantages of the traditional energy supply systems, such as separate planning, separate design, independent operating mode, and the increasingly prominent nonlinear coupling between various sub-systems, the production, transmission, storage and consumption… read more here.
Keywords: state; energy; method; state estimation ... See more keywords
Cubic Observers for State Estimation of Nonlinear Systems
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Control, Automation and Electrical Systems"
DOI: 10.1007/s40313-021-00758-1
Abstract: This paper extends the usage of a recently introduced state observer; the cubic observer, to a relatively large family of nonlinear dynamical systems including one-sided Lipschitz and Lipschitz systems as special cases. Convergence criteria as… read more here.
Keywords: systems cubic; state estimation; observers state; state ... See more keywords
A state estimation approach based on stochastic expansions
Sign Up to like & getrecommendations! Published in 2018 at "Computational and Applied Mathematics"
DOI: 10.1007/s40314-017-0515-0
Abstract: This paper presents a new approach for state estimation problems. It is based on the representation of random variables using stochastic functions. Its main idea is to expand the state variables in terms of the… read more here.
Keywords: state; state estimation; approach; estimation approach ... See more keywords
Nonlinear state estimation with delayed measurements using data fusion technique and cubature Kalman filter for chemical processes
Sign Up to like & getrecommendations! Published in 2019 at "Chemical Engineering Research and Design"
DOI: 10.1016/j.cherd.2018.11.020
Abstract: Abstract Nonlinear state estimation with delayed measurements has been considered in many industrial applications. However, classical methods cannot use these slow rates, irregular, delayed measurements, even though the delayed measurements are usually more accurate. Therefore,… read more here.
Keywords: nonlinear state; data fusion; state estimation; delayed measurements ... See more keywords
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