Results 151 to 160 of about 46,986 (307)

Adaptive feedforward control of closed orbit distortion caused by fast helicity-switching undulators. [PDF]

J Synchrotron Radiat, 2021
Masaki M, Maesaka H, Soutome K, Takano S, Watanabe T, Kubota K, Fujita T, Dewa H, Fukui T, Sugimoto T, Takeuchi M, Tanaka H.   +11 more
europepmc   +1 more source

Control Parameters Design of Spraying Robots Based on Dynamic Feedforward

The positioning and velocity accuracy of spraying robots determine the quality of the coating, and the influence of the robotic dynamic characteristics on control precision is significant.
Yanbing Liu, Jianwan Ding, Yu Chen, Liping Chen, Dong Yan   +4 more
core   +1 more source

Practical tuning guide to mixed feedback and feedforward control of soft-mounted vibration isolators

, 2016
This paper proposes a practical tuning guide for mixed feedback and feedforward control design of active soft-mounted vibration isolators. A model is derived based on measured frequency response function data obtained from an industrial vibration ...
Butler, H., Heertjes, MF Marcel, Steinbuch, M Maarten, Beijen, M.A., Steinbuch, M., Heertjes, M.F., Butler, H Hans, Beijen, MA Michiel, Steinbuch, M.; id_orcid   +8 more
core   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source

Does a Feedforward Orientation Provide Competitive Advantages Under Disruptive Conditions? A Review of Control Literature with an Illustrative Case

Administrative Sciences
This paper identifies the salient features of feedforward control and the advantages that it provides vis-à-vis feedback control. These advantages are especially salient in strategic control situations and also during periods of environmental turbulence ...
Rajaram Veliyath
doaj   +1 more source

Combined Feedback Feedforward Control of a 3-Link Musculoskeletal System Based on the Iterative Training Method. [PDF]

Biomed Res Int, 2021
Valizadeh A, Akbari AA.
europepmc   +1 more source

Jerk derivative feedforward control for motion systems

, 2004
This work discusses reference trajectory relevant model based feedforward design. For motion systems which contain at least one rigid body mode and which are subject to reference trajectories with mostly low frequency energy, the proposed feedforward ...
Steinbuch, M Maarten, Boerlage, M.L.G., Tousain, R.L., Steinbuch, M., Boerlage, MLG Matthijs, Tousain, RL Rob, Steinbuch, M.; id_orcid   +6 more
core  

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

The Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin, Clémence Fauteux‐Lefebvre, Jules Thibault   +2 more
wiley   +1 more source

Accuracy aspects in motion feedforward tuning

, 2014
Feedforward control can significantly improve the performance of a motion system through compensation of known disturbances. Recently, new feedforward algorithms have been proposed that exploit measured data from previous tasks and a suitable feedforward
Steinbuch, M Maarten, Boeren, F.A.J., Steinbuch, M., Oomen, T.A.E., Frank Boeren, Boeren, FAJ Frank, Oomen, TAE Tom, Maarten Steinbuch, Tom Oomen, Steinbuch, M.; id_orcid   +9 more
core   +1 more source

DinoFlow: Self‐supervised pretraining in flow cytometry enables accurate detection of common hematopathological disorders

Cytometry Part B: Clinical Cytometry, EarlyView.
Abstract Flow cytometry is an essential component of routine hematological lab testing. Many computational methods have been proposed for the analysis of flow cytometry data, but most have focused on supervised learning for just one or a few specific disorders.
Brendan O'Fallon, Muir Morrison, Mattia Medina Grespan, Nicholas C. Spies, David P. Ng   +4 more
wiley   +1 more source