Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCA.2013.6565139
Title: Robust identification of piecewise affine systems from noisy data
Authors: Yang, Y.
Xiang, C. 
Lee, T.H. 
Issue Date: 2013
Source: Yang, Y.,Xiang, C.,Lee, T.H. (2013). Robust identification of piecewise affine systems from noisy data. IEEE International Conference on Control and Automation, ICCA : 646-651. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCA.2013.6565139
Abstract: In this paper, we focus on the identification of discrete-time piecewise affine (PWA) systems from noisy data. This problem consists of the estimation of both the local affine subsystems and the partition of the regression space. A two-stage robust identification approach is proposed to estimate the local affine subsystems in the presence of noise. This approach includes an optimization-based initial estimation process and a least-squares-based refinement procedure. In addition, to estimate the partition of the regression space for continuous dynamic PWA systems, an intersection approach is proposed as an alternative to the widely used pattern recognition approaches. Simulation studies demonstrate the effectiveness of the two-stage identification approach and the intersection approach in noisy case. © 2013 IEEE.
Source Title: IEEE International Conference on Control and Automation, ICCA
URI: http://scholarbank.nus.edu.sg/handle/10635/51243
ISBN: 9781467347075
ISSN: 19483449
DOI: 10.1109/ICCA.2013.6565139
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