Robust Kalman filter-based least squares identification of a multivariable system
Sign Up to like & getrecommendations! Published in 2018 at "Iet Control Theory and Applications"
DOI: 10.1049/iet-cta.2017.0829
Abstract: A novel direct identification using the residual model of Kalman filter (KF) is proposed for multiple-input and multiple-output Box–Jenkins model of the system formed of the signal and disturbance models using the residual model relating… read more here.
Keywords: system; least squares; kalman filter; residual model ... See more keywords
Uncertainty Analysis of Scattering Parameters Calibrated by an Electronic Calibration Unit Based on a Residual Model
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3141310
Abstract: We propose a new residual model to analyze the uncertainty of scattering parameters (S-parameters) calibrated by an electronic calibration unit (ECU). Residual errors are usually estimated from the observed ripple after connecting a load or… read more here.
Keywords: residual model; calibration; uncertainty; scattering parameters ... See more keywords
Detection of Small-Sized Insects in Sticky Trapping Images Using Spectral Residual Model and Machine Learning
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Plant Science"
DOI: 10.3389/fpls.2022.915543
Abstract: One fundamental component of Integrated pest management (IPM) is field monitoring and growers use information gathered from scouting to make an appropriate control tactics. Whitefly (Bemisia tabaci) and thrips (Frankliniella occidentalis) are two most prominent… read more here.
Keywords: spectral residual; insects; small sized; detection ... See more keywords
Model Predictive Controller Design Based on Residual Model Trained by Gaussian Process for Robots
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Marine Science and Engineering"
DOI: 10.3390/jmse11050893
Abstract: Model mismatch is inevitable in robot control due to the presence of unknown dynamics and unknown perturbations. Traditional model predictive control algorithms are usually based on constant value assumptions and are not able to overcome… read more here.
Keywords: gaussian process; robot; model; residual model ... See more keywords