title: Optimization Control of the Color-Coating Production Process for Model Uncertainty.
abstract: Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.
authors.affiliation: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, China; State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110004, China.
authors.forename: Dakuo
authors.initials: D
authors.lastname: He
authors.affiliation: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, China.
authors.forename: Zhengsong
authors.initials: Z
authors.lastname: Wang
authors.affiliation: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, China.
authors.forename: Le
authors.initials: L
authors.lastname: Yang
authors.affiliation: College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, China; State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110004, China.
authors.forename: Zhizhong
authors.initials: Z
authors.lastname: Mao
mesh_terms: D002626:Chemistry, Pharmaceutical; D003116:Color; D017143:Fuzzy Logic; D006801:Humans; D008962:Models, Theoretical; D015203:Reproducibility of Results; D035501:Uncertainty