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Drying Technology
An International Journal
Volume 41, 2023 - Issue 7
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Research Articles

Predictive control of microwave hot-air coupled drying model based on GWO-BP neural network

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Pages 1148-1158 | Received 18 Jul 2022, Accepted 09 Sep 2022, Published online: 22 Sep 2022
 

Abstract

A GB-MPC control algorithm (GWO-BP-MPC) was proposed to solve the problem of precise temperature control of fruit and vegetable coupling drying devices. Firstly, the BP (Back Propagation) neural network was improved using the Grey Wolf Optimizer (GWO) algorithm to increase the relevance and accuracy of the prediction model. By means of an improved neural network, we developed a high-accuracy predictive model for temperature control of drying units. Secondly, the projection conjugate gradient method was proposed for nonlinear optimization of the control system to improve the solving speed and accuracy of the optimal solution. The GB-MPC control algorithm was compared with the PID controller. The experimental results shown that the convergence speed of GB-MPC control was faster, the time took to reach a steady state in a single stage was shortened by 47 seconds compared with PID control. In the control process, the temperature change range of the GB-MPC control algorithm was smaller and there was no overshoot problem, which gave a better control effect than PID.

Disclosure of interest statement

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Additional information

Funding

This work was supported by Shandong Provincial Natural Science Foundation (Project no.ZR2021ME018), Guangdong Province Key Field Research and Development Plan (Project no.2018B020241003-09), Shandong Province Agricultural Machinery Equipment Research and Development Innovation Plan (Project no.2018YZ002), National Peanut Industry Technology System (CARS-13-Mechanized Sowing and Field Management Positions) China Construction Zhongxin Construction Engineering Co., Ltd. (Project no. ZX&AZ02202200016001). Natural Science Foundation of Shandong Province.

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