Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
405288 | Knowledge-Based Systems | 2011 | 11 Pages |
Polymerization kettle is the key controlled plant in ACR (Acrylate Copolymer Resin) production, which is a nonlinear time-delay system with parametric variance. However, modeling difficulties make the plant dynamic model poorly defined. A hybrid intelligent control scheme including an intelligent predictor is designed for this complex plant based on time-delay compensation theory. It consists of a Smith neural-network predictor and a self-adjusting-scaling-factor fuzzy logic controller. The simulation experiments verified the performance of our proposed system in two scenarios: one with invariant parameters and the other with time-varying parameters. Moreover, the comparison to other three typical control methods including Smith PID, Smith neural-network PID and Smith fuzzy logic control is also presented, which demonstrates that the proposed control scheme has satisfactory effect. Even when the system parameters vary with time, the proposed system still gives superior performance and improved robustness.