Abstract
The stability of outlet moisture content of primary tobacco processing is an indicator that the tobacco industry is very concerned about. In view of the problems that most of the existing control methods need to rely on artificial experience and complex mechanism modeling, a control method of outlet moisture content of tobacco primary processing based on TVA- TCN-MPC is proposed. Firstly, the TVA- TCN outlet moisture prediction model is established with the input moisture, water addition coefficient, and outlet moisture as input. Then, its output is used as the input of the objective optimization function, which is constrained by the control error and the adjustment range of the water addition coefficient, so that the control problem is transformed into the problem of solving the objective function, and the local optimal control sequence is obtained. And then continuously rolling optimization to achieve the target outlet moisture. Experiments are carried out on the actual data of cigarette factory, and the outlet moisture control algorithm based on TVA- TCN-MPC can effectively improve the stability of outlet moisture.
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