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A Model Predictive Control of a Grain Dryer with Four Stages Based on Recurrent Fuzzy Neural Network
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A Model Predictive Control of a Grain Dryer with Four Stages Based on Recurrent Fuzzy Neural Network
Chunyu Zhao21  , Qinglei Chi21 , Lei Wang22 and Bangchun Wen21
| (21) |
School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110004, P.R. China |
| (22) |
Shenyang Neusoft Software Co.ltd, Shenyang 110179, P.R. China |
Abstract
This paper proposes a model predictive control scheme with recurrent fuzzy neural network (RFNN) by using the temperature
of the drying process for grain dryers. In this scheme, there are two RFNNs and two PI controllers. One RFNN with feedforeward
and feedback connections of grain layer history position states predicts outlet moisture content (MPRFNN), and the other predicts
the discharge rate of the dryer (RPRFNN). One PI controller adjusts the objective of the discharge rate by using MPRFNN, and
the other adjusts the given frequency of the discharge motor to control the discharge rate of the grain dryer to reach its
objective by using RPRFNN. The experiment is carried out by applying the proposed scheme on the control of a gain dryer with
four stages to confirm its effectiveness.
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