论文标题
在线计算分布式模型中的终端成分用于参考跟踪的预测性控制
Online Computation of Terminal Ingredients in Distributed Model Predictive Control for Reference Tracking
论文作者
论文摘要
开发了一个分布式模型预测控制方案，用于跟踪终端集在线重新配置的分段常数参考，而端子控制器是离线计算的。与许多标准现有方案不同，该方案在不执行离线集中计算的情况下产生大型可行区域。尽管所得的最佳控制问题（OCP）是半决赛程序（SDP），但基于对角线优势的SDP可伸缩方法用于通过二阶锥形程序近似派生的SDP。所提出的方案及其近似的OCP可以正常进行分布式优化。使用电源网络示例评估这两个方案，并将其与在线重新配置的方案进行比较。发现固定终端控制器会导致更好的性能，明显的计算成本降低以及与该控制器在线重新配置的情况相比，相似的可行区域。
A distributed model predictive control scheme is developed for tracking piecewise constant references where the terminal set is reconfigured online, whereas the terminal controller is computed offline. Unlike many standard existing schemes, this scheme yields large feasible regions without performing offline centralized computations. Although the resulting optimal control problem (OCP) is a semidefinite program (SDP), an SDP scalability method based on diagonal dominance is used to approximate the derived SDP by a second-order cone program. The OCPs of the proposed scheme and its approximation are amenable to distributed optimization. Both schemes are evaluated using a power network example and compared to a scheme where the terminal controller is reconfigured online as well. It is found that fixing the terminal controller results in better performance, noticeable reduction in computational cost and similar feasible region compared to the case in which this controller is reconfigured online.
