Alshahed, Osamh S., Kaur, Baldeep ORCID: https://orcid.org/0000-0002-1762-3058, Bradley, Michael S.A. and Armour-Chelu, David (2024) Data-driven system identification and model predictive control of pneumatic conveying using nonlinear dynamics analysis for optimised energy consumption. Powder Technology, 449:120364. ISSN 0032-5910 (Print), 1873-328X (Online) (doi:10.1016/j.powtec.2024.120364)

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Abstract

Pneumatic conveying systems provide secure transportation of particulate material and a dust-free environment. These systems face high energy consumption, material degradation, and pipeline blockages. This research presents an innovative solution by integrating nonlinear dynamics analysis of electrostatic sensor data, including chaos and recurrence quantification analysis, sparse identification of nonlinear dynamics with control (SINDYc) and model predictive control (MPC). The Lyapunov exponent, approximate entropy and recurrence rate of electrostatic sensor data reveal the chaotic nature of gas-solid flows. MPC framework was tailored for real-time optimisation of a pneumatic conveying system. SINDYc system models were developed using data collected from an open-loop control pneumatic conveying process to conduct MPC simulations and select an appropriate model for real-time control. This research illustrates the potential of integrating nonlinear dynamics analysis, SINDYc integrated and MPC for enhanced system performance, showcased a significant reduction in energy consumption without compromising the system's efficiency or reliability.

Item Type:	Article
Uncontrolled Keywords:	pneumatic conveying, chaos analysis, recurrence quantification analysis, sparse identification of nonlinear dynamics, model predictive control
Subjects:	Q Science > Q Science (General) T Technology > T Technology (General) T Technology > TP Chemical technology
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 16:24
URI:	http://gala.gre.ac.uk/id/eprint/48379

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