基于变更设计的数据驱动产品供应链系统预测控制

Data-driven Based Predictive Control for Supply Chain Systems Subject to Design Change

针对突发事件导致的产品供应链系统设计变更问题,设计一种基于数据驱动的预测控制算法,使产品生产满足用户的不确定需求。首先,根据产品供应链系统各部分之间的协作关系,将系统建模为多智能体系统,供应链系统设计变更描述为多智能体系统的拓扑结构切换。其次,设计了一种分布式无模型自适应预测控制方法,使供应链系统中的生产率水平能够满足用户需求。再次,引入了未来时刻的输入输出,算法设计可以使产品供应链系统预测未来一段时间内生产满足的库存水平。最后,对算法的稳定性进行了分析,并通过数值模拟仿真验证了所提出算法的有效性。结果表明,该方法可以有效控制产品供应链系统的生产供应,使得变更发生后的生产水平满足市场需求。

Aiming at the design change problem caused by unexpected events for production and supply chain system,a data-driven predictive control algorithm was designed to meet the uncertain the customers demands.Firstly,the production and supply chain system was modeled as a multi-agent system according to the collaboration relationship among the agents.Secondly,a distributed model-free adaptive predictive control algorithm was designed to enable the production inventory level in the supply chain system to meet the customers demands.Thirdly,by introducing the input and output data of future moments,the algorithm design for product and supply chain system can predict the inventory level in the future period.Finally,the convergence of the algorithm was analyzed and effectiveness of the proposed algorithm was verified by numerical simulation.The results show that the propose method can effectively control the productivity of the system,so that the production inventory level after change meets the market demand.