文献类型：期刊文献

英文题名：A Utility-Aware Probabilistic Digital Twin Framework With CC-MPC for Hard-Compliance Real-Time Decision Support in Continuous-Flow Environmental Treatment

作者：Pan, Keqiang Shen, Xin Li, Shuwen

第一作者：潘克强;Pan, Keqiang

通信作者：Pan, KQ[1];Pan, KQ[2]

机构：[1]Guizhou Univ, Sch Mech Engn, Guiyang 550025, Peoples R China;[2]Guizhou Inst Technol, Sch Mech Engn, Guiyang 550025, Peoples R China;[3]Guizhou Coll Elect Sci & Technol, Dept Intelligent Mfg, Guiyang 561113, Peoples R China

第一机构：Guizhou Univ, Sch Mech Engn, Guiyang 550025, Peoples R China

通信机构：corresponding author), Guizhou Univ, Sch Mech Engn, Guiyang 550025, Peoples R China;corresponding author), Guizhou Inst Technol, Sch Mech Engn, Guiyang 550025, Peoples R China.|贵州理工学院机械工程学院;贵州理工学院;

年份：2026

卷号：14

起止页码：71678-71689

外文期刊名：IEEE ACCESS

收录：;EI(收录号：20262020734793);Scopus(收录号：2-s2.0-105039132743);WOS:【SCI-EXPANDED(收录号:WOS:001767283200039)】；

基金：This work was supported in part by Guizhou Institute of Technology under Contract GZLGXM-09.

语种：英文

外文关键词：Modeling; Costing; Costs; Calibration; Measurement; Digital twins; Protocols; Runtime; Optimization; Uncertainty; Probabilistic digital twin; chance-constrained model predictive control; uncertainty quantification; parameter drift; calibration; compliance-gated evaluation; environmental treatment

摘要：Compliance-critical environmental treatment units must satisfy hard discharge limits while operating under time-varying disturbances and model uncertainty. This paper presents a utility-aware probabilistic digital twin (PDT) framework that couples online Bayesian uncertainty maintenance with chance-constrained model predictive control (CC-MPC) for minute-level decision support. The PDT maintains a posterior over uncertain process parameters using sequential Bayesian filtering, which induces calibrated predictive distributions for compliance-relevant variables. CC-MPC then selects dosing actions by enforcing chance constraints on the predicted discharge quality while minimizing expected operating cost. To enable reproducible and decision-relevant comparisons under practical data-confidentiality constraints, we introduce a compliance-gated utility-aware evaluation protocol: implementations must first pass explicit compliance gates before utility (cost) is compared, and calibration is reported as a necessary diagnostic. A numerical study based on anonymized/simulated minute-level signals, including an injected drift event, demonstrates the end-to-end workflow, reports compliance and cost outcomes, and quantifies computational load for real-time feasibility.