An Integer Programming Approach for Analyzing the Measurement Redundancy in Structured Linear Systems

A linear system whose model matrix is of size n×p is considered structured if some p row vectors in the model matrix are linearly dependent. Computing the degree of redundancy for structured linear systems is proven NP-hard. Previous computation strategy is divide-and-conquer, materialized in a bound-and-decompose algorithm, which, when the required conditions are satisfied, can compute the degree of redundancy on a set of much smaller submatrices instead of directly on the original model matrix. The limitation of this algorithm is that the current decomposition conditions are still restrictive and not always satisfied for many applications. We present a mixed integer programming (MIP) formulation of the redundancy degree problem and solve it using an existing MIP solver. Our numerical studies indicate that our approach outperforms the existing methods for many applications, especially when the decomposition conditions are not satisfied. The main contribution of the paper is that we tackle this challenging problem from a different angle and test a promising new approach. The resulting approach points to a path that can potentially solve the problem in its entirety.

[1]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice , 1993 .

[2]  Yong Chen,et al.  On the (co)girth of a connected matroid , 2007, Discret. Appl. Math..

[3]  Yong Chen,et al.  Robust Calibration for Localization in Clustered Wireless Sensor Networks , 2007, 2007 IEEE International Conference on Automation Science and Engineering.

[4]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988, Wiley interscience series in discrete mathematics and optimization.

[5]  Yong Chen,et al.  On the ( co ) girth of connected matroids ? , 2006 .

[6]  J. Levine,et al.  On fault-tolerant observers , 1989, Proceedings. ICCON IEEE International Conference on Control and Applications.

[7]  Jim Hefferon,et al.  Linear Algebra , 2012 .

[8]  Ümit V. Çatalyürek,et al.  Permuting Sparse Rectangular Matrices into Block-Diagonal Form , 2004, SIAM J. Sci. Comput..

[9]  Martin W. P. Savelsbergh,et al.  Progress in Linear Programming-Based Algorithms for Integer Programming: An Exposition , 2000, INFORMS J. Comput..

[10]  W. Rugh Linear System Theory , 1992 .

[11]  Brian W. Kernighan,et al.  AMPL: A Modeling Language for Mathematical Programming , 1993 .

[12]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988 .

[13]  Shankar Narasimhan,et al.  Redundant sensor network design for linear processes , 1995 .

[14]  Lamine Mili,et al.  Robust state estimation of electric power systems , 1994 .

[15]  Abdel Aitouche,et al.  Sensor network design for fault tolerant estimation , 2004 .

[16]  W. Greub Linear Algebra , 1981 .

[17]  G. Nemhauser,et al.  Integer Programming , 2020 .

[18]  Tamar Frankel [The theory and the practice...]. , 2001, Tijdschrift voor diergeneeskunde.

[19]  Yong Chen,et al.  Calculating the Breakdown Point of Sparse Linear Models , 2009, Technometrics.