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作 者:任超 王凯[1] 韩洁[1] 阳春华[1] REN Chao;WANG Kai;HAN Jie;YANG Chunhua(School of Automation,Central South University,Changsha 410083,Hunan,China)
出 处:《化工学报》2025年第1期256-265,共10页CIESC Journal
基 金:国家重点研发计划项目(2022YFB3305900);中南大学研究生科研创新项目(2024ZZTS0098)。
摘 要:流程工业中的慢时变现象普遍存在,持续变化的工况会导致生产调度的最优操作条件偏移,原有的决策方案不再适用。提出了一种基于事件-时间触发的动态调度方法。首先,分析了慢时变参数对长周期调度决策的影响,提出以操作变量的变化表征设备性能衰减的策略,并构建了动态触发函数,在动态调度的触发条件中融合了事件和时间触发的特点,设计了时变约束条件。其次,在调度过程中嵌入生产系统的动态信息,建立了过程过渡模型作为输入输出动力学的简化表达,从而降低了计算的复杂度。最后,采用闭环滚动的动态调度框架,依据实时的运行状态更新调度模型。在示例研究中,以工业换热网络为例验证了所提方法的有效性,该方法能提供及时的动态调度,表现出较好的经济性能,为考虑工况随时间缓慢迁移条件下的生产调度问题提供了新的解决方案。In process industries,the phenomenon of slow time-varying transitions is prevalent.Continuous changes in operating conditions will lead to shifts in the optimal operating conditions for production scheduling,rendering original decision schemes inapplicable.Therefore,in this paper,a dynamic scheduling method based on event-time triggering mechanism is proposed.First,the impact of slow time-varying parameters on long-term scheduling decisions is analyzed.A strategy is proposed to characterize equipment performance degradation through changes in operational variables,and a dynamic triggering function is constructed.The dynamic scheduling trigger conditions integrate event and time-triggered characteristics,incorporating time-varying constraints.Secondly,dynamic information of the production system is embedded in the scheduling process.A process transition model is established as a simplified expression of input-output dynamics,thereby reducing computational complexity.Finally,a dynamic scheduling framework of closed-loop rolling is used to update the scheduling model according to the real-time operating status.In the case study,the proposed method is validated using an industrial heat exchanger network.This method provides timely dynamic scheduling,demonstrates good economic performance,and offers a new solution for production scheduling problems considering slow time-varying operating conditions.
关 键 词:过程系统 动态调度 事件-时间触发 滚动优化 换热网络
分 类 号:TB114.1[理学—运筹学与控制论] TP273[理学—概率论与数理统计]
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