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Open AccessArticle

A CS Recovery Algorithm for Model and Time Delay Identification of MISO-FIR Systems

by Yanjun Liu 1,2,* and Taiyang Tao 2
1
Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China
2
School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
*
Author to whom correspondence should be addressed.
Academic Editor: Paul M. Goggans
Algorithms 2015, 8(3), 743-753; https://doi.org/10.3390/a8030743
Received: 29 June 2015 / Revised: 6 August 2015 / Accepted: 2 September 2015 / Published: 10 September 2015
This paper considers identifying the multiple input single output finite impulse response (MISO-FIR) systems with unknown time delays and orders. Generally, parameters, orders and time delays of an MISO system are separately identified from different algorithms. In this paper, we aim to perform the model identification and time delay estimation simultaneously from a limited number of observations. For an MISO-FIR system with many inputs and unknown input time delays, the corresponding identification model contains a large number of parameters, requiring a great number of observations for identification and leading to a heavy computational burden. Inspired by the compressed sensing (CS) recovery theory, a threshold orthogonal matching pursuit algorithm (TH-OMP) is presented to simultaneously identify the parameters, the orders and the time delays of the MISO-FIR systems. The proposed algorithm requires only a small number of sampled data compared to the conventional identification methods, such as the least squares method. The effectiveness of the proposed algorithm is verified by simulation results. View Full-Text
Keywords: compressed sensing; sparse; parameter identification; gradient projection pursuit algorithm; time delay estimation compressed sensing; sparse; parameter identification; gradient projection pursuit algorithm; time delay estimation
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Liu, Y.; Tao, T. A CS Recovery Algorithm for Model and Time Delay Identification of MISO-FIR Systems. Algorithms 2015, 8, 743-753.

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