Identification of switched FIR systems with random missing outputs: A variational Bayesian approach |
| |
| Authors: | Xinpeng Liu Xianqiang Yang Miao Yu |
| |
| Institution: | 1. Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, China;2. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China;1. School of Automation, Northwestern Polytechnical University, Xi’an 710072, PR China;2. Key Laboratory of Information Fusion Technology, Ministry of Education, Xi’an 710072, PR China;1. School of Science, Jiangnan University, Wuxi 214122, PR China;2. Nanjing Software Institute, Jinling Institute of Technology, Nanjing 211169, PR China;3. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, PR China;4. College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, PR China;1. School of Astronautics, Harbin Institute of Technology, Harbin 150001, China;2. Graduate School of Science and Technology, Tokai University 9-1-1, Toroku, Kumamoto 862-8652, Japan |
| |
| 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. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
