Model predictive control simulation of pneumatic conveying of plastic pellets using nonlinear dynamics analysis and sparse identification of nonlinear dynamics with control
Tools
Tools
Alshahed, Osamh Sabri Mohammed Atia, Kaur, Baldeep
ORCID: 0000-0002-1762-3058
, Bradley, Michael and Armour-Chelu, David
(2024)
Model predictive control simulation of pneumatic conveying of plastic pellets using nonlinear dynamics analysis and sparse identification of nonlinear dynamics with control.
In: CHoPS 2024: 11th International Conference on Conveying and Handling of Particulate Solids, 2nd - 4th Sep., 2024, Edinburgh.
|
PDF (Extended Abstract)
47922_ALSAHED_Model_predictive_control_simulation_of_pneumatic_conveying_of_plastic_pellets_using_nonlinear_dynamics_analysis_and_sparse_identification_of_nonlinear_dynamics_with_control_ABSTRACT.pdf - Published Version Download (505kB) | Preview |
Abstract
The study explores the integration of Model Predictive Control (MPC) and Sparse Identification of Nonlinear Dynamics with control (SINDYc) with nonlinear dynamics analysis to simulate the pneumatic conveying of plastic pellets. Nonlinear dynamics analysis measures were applied to data from a bottom arc-shaped electrostatic sensor of fully developed gas-solid flow in horizontal pipelines, including Lyapunov exponents, approximate entropy and recurrence rate. The study leverages SINDYc, a data-driven method, to identify sparse system models using the analysis measures. The MPC framework is then employed to optimise control inputs over a future horizon, ensuring desired nonlinear flow behaviour. The simulation framework assesses MPC's performance, using three distinct SINDYc models for each analysis measure to understand their control system's dynamics. Results showcase the ability to integrate MPC and SINDYc with the nonlinear dynamics analysis measures, highlighting improvements in system control.
| Item Type: | Conference or Conference Paper (Paper) |
|---|---|
| Uncontrolled Keywords: | pneumatic conveying, model predictive control, sparse identification of nonlinear dynamics with control, chaos analysis, recurrence analysis |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics T Technology > T Technology (General) |
| Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science Faculty of Engineering & Science > School of Engineering (ENG) Faculty of Engineering & Science > Wolfson Centre for Bulk Solids Handling Technology |
| Last Modified: | 22 Oct 2024 16:53 |
| URI: | http://gala.gre.ac.uk/id/eprint/47922 |
Actions (login required)
 |
View Item |
Downloads
Downloads per month over past year