Abstract
As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. In this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refining system, and then the Wiener-Type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. Finally, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.
Original language | English |
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Article number | 8046139 |
Pages (from-to) | 1208-1215 |
Number of pages | 8 |
Journal | IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans |
Volume | 50 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2020 |
Externally published | Yes |
Funding
Manuscript received March 9, 2017; revised May 15, 2017; accepted August 18, 2017. Date of publication September 19, 2017; date of current version February 19, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61473064, Grant 61621004, and Grant 61333007, and in part by the Research Funds for the Central Universities under Grant N160805001 and Grant N160801001. This paper was recommended by Associate Editor J.-H. Chou. (Corresponding author: Ping Zhou.) M. Li, P. Zhou, and T. Chai are with the State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China (e-mail: [email protected]; [email protected]; [email protected]).
Keywords
- High consistency (HC) refining system
- nonlinear multiobjective model predictive control (MPC)
- optimal operation
- pulp quality
- specific energy (SE) consumption