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Journal of System Simulation

Abstract

Abstract: An adaptive blending optimization system based on five-dimensional digital twin theory is designed and developed to address the challenges of strict nonlinear constraints and frequent raw material fluctuations. A five-dimensional model architecture is constructed to achieve virtual-real mapping and synergy throughout the blending process. A closed-loop control strategy of "online model correction and dynamic recipe optimization" is proposed. The constrained recursive least squares (RLS) algorithm is adopted to update the octane blending effect model parameters, resolving the model mismatch caused by raw material fluctuations. The linear decreasing weight particle swarm optimization algorithm (LDW-PSO) is combined to determine the optimal recipe under multiple constraints, thereby improving optimization accuracy and algorithm stability. Simulation results demonstrate that the system communication latency is less than 250 ms. It supports real-time monitoring and dynamic optimization for large time-delay processes, effectively suppresses raw material disturbances, and achieves boundary control of key indicators. This system provides a controllable and visible optimization paradigm for intelligent refineries.

First Page

2840

Last Page

2856

CLC

TP273; TP391.9

Recommended Citation

Fang Yaning, He Renchu. Five-dimensional Digital Twin System for Closed-loop Gasoline Blending Optimization[J]. Journal of System Simulation, 2026, 38(10): 2840-2856.

Corresponding Author

He Renchu

DOI

10.16182/j.issn1004731x.joss.26-0102

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