化工学报2013，Vol.64Issue(4)：1318-1331,14.DOI:10.3969/j.issn.0438-1157.2013.04.028
分布式预测控制全局协调及稳定性分析
Global coordination and stability analysis for distributed model predictive control system
摘要
Abstract
With the high dimension in chemical processes, it is necessary to coordinate the sub-systems to achieve optimality of the global system after decomposing the large-scale system. The on-line optimization of the whole system is decomposed into several small sub-problems, significantly reducing the computational complexity in model predictive control of the large-scale system. Decentralized model predictive control and the neighborhood optimization algorithm for distributed model predictive control based on the cascade process are not suitable for the chemical process containing interactive feedback. Therefore, by taking the system constraints into account, the global coordination algorithm was deduced based on those two optimization algorithms. The large-scale system was decomposed into sub-systems with lower dimension. Assumably there was one sample time delay communication between interacted subsystems. For each sub-system, the predictive model was constructed and the overall objective function was formulated by considering the interactions of the sub-systems. The optimal control of each sub-system was achieved. Then, the consistency for distributed model predictive control based on global coordination and centralized model predictive control was analyzed under certain conditions. The global stability of the closed loop system with distributed model predictive control based on global coordination was also obtained. The proposed algorithm was tested by simulation study of Shell heavy oil fractionator and TE process. When compared with other algorithms, it was feasible and effective.关键词
大系统/分布式控制/预测控制/全局协调/稳定性分析Key words
large scale system/ distributed control system/ model predictive control/ global coordination/ stability analysis分类
信息技术与安全科学引用本文复制引用
刘雨波,罗雄麟,许锋..分布式预测控制全局协调及稳定性分析[J].化工学报,2013,64(4):1318-1331,14.基金项目
国家自然科学基金项目(21006127) （21006127）
国家重点基础研究发展计划项目(2012CB720500). （2012CB720500）
