Research on the Control System of Mobile Straw Compaction Molding Machine Based on Pso-elm-gpc Model
Year: 2024
Type: article
Abstract: To address the issue of mutual influence and coupling between the main shaft speed and feeding amount of the mobile straw compaction molding machine, which is beneficial for the intelligent operation of the compaction molding, this paper designs a PSO-ELM-GPC control model. This model integrates Particle Swarm Optimization (PSO) algorithm, Extreme Learning Machine (ELM), and Generalized Predictive Control (GPC). It uses the ELM optimized by PSO to predict the output of the main shaft speed and feeding amount, and adjusts the input of the GPC controller based on the deviation weight adjustment unit. Field simulation experiments show that the maximum dynamic deviation of the speed is 1.72%, and the deviation from the target value is 1.52%. The maximum dynamic deviation of the feeding amount is 1.22%, and the deviation from the target value is 1.42%. The PSO-ELM-GPC model designed in this paper can promptly correct the uncertainties in speed and feeding amount control caused by disturbances.
Source: INMATEH Agricultural Engineering
Authors: Huiying CAI, Yunzhi LI, Fangzhen LI
Institution: Shandong University of Finance and Economics
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405664742