Efficient identification of Wiener systems using a combination of atomic norm minimization and interval matrix properties
Efficient identification of Wiener systems using a combination of atomic norm minimization and interval matrix properties
复制标题
使用原子范数最小化和区间矩阵属性的组合有效识别维纳系统
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
M. Sznaier
中科院分区：
文献类型：
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作者：
Burak Yılmaz;M. Sznaier
即使在已知非线性的情况下，面向控制的维纳系统辨识也是一个一般的np困难问题。虽然问题的凸松弛是可用的，但这些也是计算密集型的，因为它们通常需要解决大量的线性规划或解决大型的半确定规划。为了克服这一困难，本文基于区间矩阵与原子范数最小化和混合二进制规划的组合性质，提出了一种替代方案。如文中所述，这种组合导致了计算效率高的算法，能够处理规模挑战现有技术的问题。
Control oriented identification of Wiener systems is known to be a generically NP-hard problem, even in cases where the nonlinearity is known. While convex relaxations of the problem are available, these are also computationally intensive, since they typically require either solving a large number of Linear Programs or solving large-sized Semi-Definite Programs. To circumvent this difficulty, in this paper we present an alternative, based on a combining properties of interval matrices with atomic norm minimization and mixed binary programming. As illustrated in the paper, this combination leads to a computationally efficient algorithm, capable of handling problems whose size challenges existing techniques.