Abstract
In this article, a two-layered model predictive control strategy is proposed for the nonsquare system of nonlinear cut tobacco drying process. The control objective is to optimize the drum dryer temperature, hot air temperature, and cut tobacco outlet temperature meet the process constraints while meeting the moisture content of cut tobacco. Firstly, the tobacco drying process system was introduced, and the nonsquare system model and performance index function were established. Then a nonlinear moving horizon estimator (NMHE) and real-time optimization (RTO) are designed. NMHE provides state and parameter estimation for the controller, and RTO provides an optimal operating setpoint for the controller. Subsequently, a two-layered model predictive control (SSTO-MPC) design integrated with a steady-state target optimization layer (SSTO) is proposed for the nonsquare system of nonlinear cut tobacco drying process. Extensive simulations under different scenarios illustrate the effectiveness of the proposed SSTO-MPC design compared with the conventional MPC.
Highlights
The main function of the cut tobacco drying process is to reduce the moisture content in cut tobacco, which is convenient for subsequent processing and storage
The results indicate that nonlinear moving horizon estimator (NMHE) provides accurate estimates of three thermal conductivity and four states, especially when the cut tobacco outlet moisture content is not measurable; it is estimated accurately
steady-state target optimization (SSTO)-model predictive control (MPC) and real-time optimization (RTO)-MPC track the optimal operating setpoints in the closed-loop simulation, as shown in figure 7. It can be seen from figure 7 that when there is a disturbance in the system, RTO-MPC still has static error control, which cannot overcome the shortcomings of the control of the nonsquare system; at the same time, the moisture of the cut tobacco outlet exceeds the operational constraints of the output variable, which affects the quality of subsequent products
Summary
The main function of the cut tobacco drying process is to reduce the moisture content in cut tobacco, which is convenient for subsequent processing and storage. A. Chen et al.: Two-Layered MPC Strategy of the Cut Tobacco Drying Process among economic and control worlds and periodically transfers all input and output steady-state operation setpoints to the lower MPC, and the task of MPC is to transfer the system from the current state to the target state. Due to the different system models used by RTO and MPC, MPC can not reach the operating setpoints of RTO optimization, resulting in a steady-state static error of system output This is another direct reason for the low energy efficiency of drying equipment [22], [23]. The simulation results under different scenarios have demonstrated that the proposed two-layered MPC based on SSTO provides a more flexible way to handle the cut tobacco drum dryer system’s optimization problem in the presence of system nonlinearities, constraints, and disturbances. The NMHE and RTO structure considered in this work are represented in figure 2
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