Identification of switched FIR systems with random missing outputs: A variational Bayesian approach. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Liu, Xinpeng; Yang, Xianqiang; Yu, Miao
• Is Part Of: Journal of the Franklin Institute. Volume 358:Issue 1(2021)
• Page Start: 1136
• Page End: 1151
• Publication Date: 2021-01
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2020.10.046
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: Identification of switched finite impulse response (FIR) systems in the presence of random missing outputs is investigated in this paper and the practical problems of unknown number of local models and unknown switching mechanism are handled. From a Bayesian perspective, the probabilistic model for describing the identification problem is constructed and the algorithm to estimate all of the unknown parameters is derived by using the variational Bayesian (VB) approach. In addition, the number of local models can be selected based on the probability of each local component, and the predicted output can be obtained as the output of the local model that takes effect. A simulated example and the mass-spring-damper system are explored to illustrate the efficacy of the developed algorithm.