1#. • Basis Weight Control System
time-varying acceleration coefficients (PSO-TVAC) [29] , and modified particle swarm optimization (MPSO) [22] . ` "ASIS` WEIGHT` CONTROL` IN` PAPERMAKING` PROCESS The evaluation of paper quality includes the basis weight of paper, moisture, ash, color, etc. The basis weight means the weight of paper per unit area expressed in g/m 2 . The smaller the basis weight fluctuation, the more uniform the paper, and the better the quality. The control of basis weight includes cross-direction (CD) basis weight control and machine-direction (MD) basis weight control. The CD basis weight control is completed by the headbox dilution water valve, while the MD basis weight control is completed by the pulp pump controlling the pulp flow. The main reasons for the MD basis weight fluctuation are the changes in paper machine speed, pulp amount, pulp concentration, etc. When the paper machine is in normal production, the paper machine speed is stable; therefore, the change in paper machine speed is generally not considered when considering the MD basis weight control. In addition to the above factors, CD basis weight fluctuation also needs to consider the interaction between dilution water valves. The basis weight control system is illustrated in Fig. 1. The pulp in the pulp tank is transported to the headbox using the pulp pump. The quality control system (QCS) calculates the difference between the value of basis weight measured by the scanner and set value, and the output controls the feeding of the pulp pump to stabilize the pulp amount, so as to achieve the effect of basis weight stability control.
The basis weight control system is a nonlinear, large, time-delay system. Flow, pressure, and other non-linear analog signals are easily subjected to electromagnetic interference during transmission, which is easy to cause detection errors, and then affects the accuracy of the identification model. Time-varying factors such as temperature change, flow jitter, and valve wear make the process object and model time-varying and uncertain. The time delay will greatly increase the control difficulty. With the demand of consumers for high-quality paper and use of advanced control technology, determining a parameter identification method to accurately identify the process model with a small time delay is the key to improving the quality of papermaking process. ` 0RINCIPLE`OF`PARAMETER`IDENTIFICATION`BASED` ON`OPTIMIZATION`ALGORITHM The block diagram of system identification based on PSO/Improved PSO (IPSO) is illustrated in Fig. 2. The purpose is to make the output y ( t ) of the selected time-delay system approach the output ŷ ( t ) of the real unknown system under the same input signal ( u /( t )). Thus, the accurate mathematical model of the real unknown system is determined, which lays a foundation for selecting the appropriate control method and designing the control system. In this study, the SNPSO is adopted to identify the unknown parameters of the transfer function FOPDT and SOPDT. The integral of absolute error (IAE) as the performance index is given by: J = ϯ 0 t e ( t ) d t (1) where e ( t ) = y ( t ) ϖ ŷ ( t ) .
'JH Ȟ Structure of basis weight control system
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