This paper investigates the adaptive model predictive control (MPC) for a class of constrained linear multiple-input multiple-output (MIMO) systems with constant parametric uncertainty and input delay. An adaptive update law based on time-varying updating rate is proposed, which enables the update of uncertain parameters in the presence of input delay. Consequently, to deal with constraints, we convert the optimization problem into a solvable simple structure, which originates from the min-max optimization. Furthermore, we theoretically show that the closed-loop system is asymptotically stable and the proposed adaptive MPC strategy is proved to be recursively feasible. Finally, numerical simulation and comparison are given to illustrate the efficacy of the proposed method.
As the main road type in an urban traffic system, the increasingly severe congestion of the expressway restricts social and economic development. It is essential to explore the evolution law of congestion and dissipation to ensure the efficient operation of the expressway. In order to accurately grasp the evolution law of the expressway traffic flow state, this paper selects the expressway weaving section, which is a traffic flow frequency-changing area, to study the traffic operation state, change process, and evolution law, and determine the traffic state discrimination standard. The simulation analysis was carried out using the traffic simulation platform, Vissim software. The simulation results showed an apparent catastrophe phenomenon in the mutual transformation between free and congestion flow. The spectral clustering analysis algorithm was used to accurately extract the boundary of traffic state mutation, combined with the cusp catastrophe theory, to study and analyze the traffic flow state at different times and positions, thus completely displaying the evolution characteristics of traffic flow state. The research results provide an essential theoretical basis for formulating control measures of expressway traffic flow and strategies for traffic congestion dissipation.
为解决全员定期核酸检测成本高,导致间隔周期长且效率低的问题,给出了基于社交网络信息的抽检策略,将在线社交网络信息与新冠肺炎传播规律融合,建立了带抽检策略的新冠肺炎传播模型.在此基础上,研究了随机抽检策略、熟人监测策略、度大节点目标抽检监测策略三种策略对新冠肺炎传播的影响.研究发现在校园等人群密集接触的环境下,熟人和度大节点目标抽检策略在峰值幅度、峰值时间、早期预警等指标下都好于随机监测策略,减少了新冠病毒传播天数以及感染人数,能更早、更快地控制住疫情,预警效果从高到低依次是度大节点目标监测策略、熟人监测策略、随机监测策略.
复杂网络的不同类型边转换(方向改变)和在不同节点间增加边对网络能控性有不同影响,为了更好地了解有向网络边转换和增加对网络能控性影响,提出一种边分类方法,把边根据节点类别和匹配关系分成12种类型,并给出辨识算法.基于此分类给出网络边转换和增加时网络能控性(驱动节点数目)的变化规律.通过模型网络和实际网络分析了每种边在网络中的比例,并分析了边转换和增加时驱动节点数目变化.结果验证了定理的正确性.
综合考虑减排投入延迟效应与消费者低碳参考效应对产品需求和品牌商誉的影响,构建了由制造商和零售商组成的双渠道低碳供应链,并基于最优控制理论先后对分散、集中和成本分担3种模式下的成员运营策略、产品低碳水平、品牌商誉以及整体利润进行了比较与分析.研究发现:参考效应总会调动制造商低碳生产的积极性,提升产品低碳水平和品牌商誉稳态值,挫伤企业广告宣传热情;只有当延迟时间低于一定阈值时,供应链成员采取集中决策才是有意义的;延迟时间抬高了消费者对产品低碳水平的心理预期;参考效应会加剧延迟时间对不同决策机制下供应链整体利润的影响.
