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This paper proposes a paddy rice model predictive control (MPC) drying strategy to achieve the real-time rolling optimization control of paddy rice intermittent drying process for the maximization of head rice yield (HRY). In the rolling optimization process, the adjusted evaluation index of predicted HRY (AEHRY) is used as the performance index to calculate the optimal control law in real-time. By comparing the simulation results of proposed drying strategies, the optimal drying strategy was chosen. Intermittent drying experiments of proposed MPC drying strategy were carried out to evaluate its performance. Experimental results showed that the proposed MPC drying strategy had the greatestAEHRYand HRY. In terms of Nanjing 9108 with initial moisture content of 22.88% wet basis, the averageAEHRYs of 50 °C, 55 °C, 60 °C constant temperature drying, and MPC drying were 0.0773, 0.2130, 0.2283 and 0.3147, with average HRYs of 0.7121, 0.7129, 0.7163 and 0.7202, respectively. The feasibility of the proposed paddy rice MPC drying strategy was proved. The paddy rice intermittent drying processes under different application conditions have different drying requirements and restrictions. By modifying constraint part of the proposed MPC drying strategy, the ranges of drying parameters and the relationship during the drying parameters can be constrained to realize the real-time online optimization of these intermittent drying processes.

Model predictive control strategy of head rice yield in paddy rice intermittent drying