Actuator Placement Under Structural Controllability Using Forward and Reverse Greedy Algorithms
Actuator Placement Under Structural Controllability Using Forward and Reverse Greedy Algorithms
复制标题
使用正向和反向贪婪算法在结构可控性下布置执行器
DOI：
10.1109/tac.2020.3044284
复制
发表时间：
2019
影响因子：
6.8
通讯作者：
M. Kamgarpour
中科院分区：
文献类型：
--
作者：
Baiwei Guo;Orcun Karaca;T. Summers;M. Kamgarpour
执行器配置是一个非常活跃的研究领域，它在复杂动态网络中的应用受到了广泛的关注。在这篇文章中，我们研究的问题，找到一组致动器的位置最小化的度量，测量由控制器的状态转移所消耗的平均能量，同时满足结构的可控性要求和允许的致动器的数量的基数约束。由于没有计算效率高的方法来解决这样的组合集函数优化问题，两个贪婪算法，向前和反向，提出了获得近似解。我们首先表明，这些算法探索的约束集的特点是拟阵。然后，我们获得性能保证的前向和反向贪婪算法应用到一般类的拟阵优化问题，通过利用属性的目标函数，如子模比和曲率。最后，我们提出了可行性检查方法，这两个算法的基础上，最大流问题的某些辅助图源自网络图。我们的研究结果验证了大型网络的案例研究。
Actuator placement is an active field of research, which has received significant attention for its applications in complex dynamical networks. In this article, we study the problem of finding a set of actuator placements minimizing the metric that measures the average energy consumed for state transfer by the controller, while satisfying a structural controllability requirement and a cardinality constraint on the number of actuators allowed. As no computationally efficient methods are known to solve such combinatorial set function optimization problems, two greedy algorithms, forward and reverse, are proposed to obtain approximate solutions. We first show that the constraint sets these algorithms explore can be characterized by matroids. We then obtain performance guarantees for the forward and reverse greedy algorithms applied to the general class of matroid optimization problems by exploiting properties of the objective function such as the submodularity ratio and the curvature. Finally, we propose feasibility check methods for both algorithms based on maximum flow problems on certain auxiliary graphs originating from the network graph. Our results are verified with case studies over large networks.
影响因子：
6.8
作者：
Menara, Tommaso;Bassett, Danielle S.;Pasqualetti, Fabio
通讯作者：
Pasqualetti, Fabio