Results 61 to 70 of about 107,979 (335)

Shaping energy cost management in process industries through clustering and soft sensors

Frontiers in Energy Research, 2023
With the ever-increasing growth of energy demand and costs, process monitoring of operational costs is of great importance for process industries.
Yu Lu, Gang Fang, Gang Fang, Daoping Huang, Daoping Huang, Baoping Cai, Hongtian Chen, Yiqi Liu, Yiqi Liu   +8 more
doaj   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Uncovering renewable energy policy impact channels on land values, the local farm structure, and farmland heterogeneity

American Journal of Agricultural Economics, EarlyView.
Abstract Germany's Renewable Energy Sources Act (REA), enacted in 2000 and subsequently amended, subsidized national renewable energy production with fixed feed‐in tariffs for renewable energy sources (RE) from wind, solar, and biogas. Empirical studies suggest that the policy was creating windfall effects for landowners and attribute farmland use ...
Lars Isenhardt, Stefan Seifert, Saskia Wolff, Tobia Lakes, Marten Graubner, Axel Werwatz, Silke Hüttel   +6 more
wiley   +1 more source

A novel online identification algorithm of lithium‐ion battery parameters and model order based on a fractional order model

IET Renewable Power Generation, 2021
A fractional order equivalent circuit model with variable order can better reflect the internal reaction mechanism of a lithium‐ion battery, however, it is not easy to simultaneously identify the parameters and order of the fractional order model online.
Xiangdong Sun, Jingrun Ji, Biying Ren, Guitao Chen, Qi Zhang   +4 more
doaj   +1 more source

A novel extended kernel recursive least squares algorithm

Neural Networks, 2012
In this paper, a novel extended kernel recursive least squares algorithm is proposed combining the kernel recursive least squares algorithm and the Kalman filter or its extensions to estimate or predict signals. Unlike the extended kernel recursive least squares (Ex-KRLS) algorithm proposed by Liu, the state model of our algorithm is still constructed ...
Zhu, Pingping, Chen, Badong, Príncipe, José C.   +2 more
openaire   +4 more sources

Adaptive mixing formation control of multiquadrotor unmanned aerial vehicle systems

Asian Journal of Control, EarlyView.
Abstract This paper presents a distributed adaptive mixing control (AMC) design for formation maintenance of systems of multiquadrotor UAVs (q‐UAVs) during commanded path‐tracking maneuvers. The proposed formation control scheme has a two‐level structure. The high level defines the desired trajectories for rigid and persistent formation acquisition and
Nasrettin Köksal, Barış Fidan, Ahmed Fahim Mostafa   +2 more
wiley   +1 more source

Modeling and parameter estimation for fractional large‐scale interconnected Hammerstein systems

Asian Journal of Control, EarlyView.
Abstract This paper addresses the challenge of modeling and identifying large‐scale interconnected systems exhibiting memory effects, hereditary properties, and non‐local interactions. We propose a fractional‐order extension of the Hammerstein architecture that incorporates Grünwald–Letnikov operators to capture complex dynamics through multiple ...
Mourad Elloumi, Omar Naifar, Imed Bouzida   +2 more
wiley   +1 more source

Performance improvement of discrete‐time linear‐quadratic regulators applied to uncertain linear systems using the Tikhonov regularization method

Asian Journal of Control, EarlyView.
Abstract The linear‐quadratic regulator (LQR) problem of optimal control of an uncertain discrete‐time linear system (DTLS) is revisited in this paper from the perspective of Tikhonov regularization. We show that an optimally chosen regularization parameter reduces, compared to the classical LQR, the values of a scalar error function, as well as the ...
Fernando Pazos, Amit Bhaya
wiley   +1 more source

Time-varying signal processing using multi-wavelet basis functions and a modified block least mean square algorithm [PDF]

, 2009
This paper introduces a novel parametric modeling and identification method for linear time-varying systems using a modified block least mean square (LMS) approach where the time-varying parameters are approximated using multi-wavelet basis functions ...
Billings, S.A., Li, Y., Wei, H.L.
core  

Transfer Learning Approaches in Bioprocess Engineering: Opportunities and Challenges

Biotechnology and Bioengineering, EarlyView.
ABSTRACT Transfer learning (TL) has recently emerged as a promising approach to overcoming one of the key limitations of bioprocess engineering: data scarcity. By leveraging knowledge from one bioprocess to another, TL allows existing models and data sets to be reused efficiently, accelerating process development, improving prediction accuracy, and ...
Daniel Barón Díaz, Anna‐Lena Drommershausen, Alexander Grünberger, Dirk Holtmann   +3 more
wiley   +1 more source