Gradient iterative algorithm for dual-rate nonlinear systems based on a novel particle filter |
| |
| Institution: | 1. School of Science, Jiangnan University, Wuxi 214122, PR China;2. College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, PR China;3. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, PR China;1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, PR China;2. College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266042, PR China;3. Nonlinear Analysis and Applied Mathematics (NAAM) Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia;4. Department of Mathematics, Quaid-I-Azam University, Islamabad 44000, Pakistan;1. Swinburne University of Technology, Hawthorn, Australia;2. Qom University of Technology, Qom, Iran;3. School of Electrical and Computer Engineering, Shiraz University, Iran |
| |
| Abstract: | This paper proposes a novel particle filter based gradient iterative algorithm for the identification of dual-rate nonlinear systems. The novel particle filter is applied to estimate the missing outputs, and the measurable outputs are utilized to adjust the weights of particles during each interval of the slow sampled rate. Then the missing outputs and the unknown parameters can be estimated iteratively by the novel particle filter based gradient iterative algorithm. The simulation results indicate that the proposed method is more effective than the classical auxiliary model method. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
