Results 81 to 90 of about 623,679 (298)
Journal of Measurement Science and Instrumentation, 2011 The performance of the conventional Kalman filter depends on process and measurement noise statistics given by the system model and measurements.The conventional Kalman filter is usually used for a linear system,but it should not be used for estimating ...
Ya-fei YANG
doaj
On the projective geometry of kalman filter [PDF]
2015 54th IEEE Conference on Decision and Control (CDC), 2015 6 ...
Francesca Paola Carli +1 more
openaire +2 more sources
Model‐Enabled Knowledge Transfer Across Cell Lines, Culture Scales and Conditions
Biotechnology and Bioengineering, EarlyView.ABSTRACT Mechanistic models are central to quantitative understanding and optimization of Chinese hamster ovary (CHO) cell culture processes, but their utility is often restricted by parameter sets calibrated for specific cell lines, scales, or operating conditions.
Luxi Yu +2 more
wiley +1 more source
Performance change detection and recovery in inferential control loops
The Canadian Journal of Chemical Engineering, EarlyView.Abstract In most industrial environments, soft sensors are crucial for estimating variables that are hard to measure. It is critical that these variables be estimated quickly and accurately because they are closely linked to plant safety and profit. Therefore, performance drift in the soft sensors cannot be ignored.
Xuanhui Zhai, Yuri A. W. Shardt
wiley +1 more source
CoRR, 2015 17 pages, 14 figures: Fixed typo in Fig.
Rahul G. Krishnan +2 more
openaire +2 more sources
The Canadian Journal of Chemical Engineering, EarlyView.Abstract Hybrid models (HMs) combine fundamental model (FM) equations with empirical components. These models can lead to improved predictions because they reduce process/model mismatch and can account for phenomena that are not considered in the FM equations.
Mouna Y. Harb, Kimberley B. McAuley
wiley +1 more source
Precision planter monitoring system based on mobile communication network
IET Networks, EarlyView., 2022 Abstract Sowing is an important link in agricultural production and the basis for ensuring high yields and bumper harvests. Agriculture requires precision plows with good performance and stable work. However, the seeding process is in a completely closed state, and the operator relies mainly on experience to judge the operating state and performance of
Bing Li, Jiyun Li
wiley +1 more source
Bayesian inverse ensemble forecasting for COVID‐19
Canadian Journal of Statistics, EarlyView.Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
wiley +1 more source
The Kalman Filter Revisited Using Maximum Relative Entropy
Entropy, 2014 In 1960, Rudolf E. Kalman created what is known as the Kalman filter, which is a way to estimate unknown variables from noisy measurements. The algorithm follows the logic that if the previous state of the system is known, it could be used as the best ...
Adom Giffin, Renaldas Urniezius
doaj +1 more source
Understanding the Kalman Filter: an Object Oriented Programming Perspective. [PDF]
The basic ideals underlying the Kalman filter are outlined in this paper without direct recourse to the complex formulae normally associated with this method. The novel feature of the paper is its reliance on a new algebraic system based on the first two
Snyder, R.D., Forbes, C.S.
core