Event-based state and fault estimation for stochastic nonlinear system with Markov packet dropout |
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| Institution: | 1. College of New Energy, China University of Petroleum (East China), Qingdao, 266580 China;2. School of Engineering & Digital Arts, University of Kent, Canterbury CT2 7NT, United Kingdom;3. Department of Electronic & Electrical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.;1. College of Mathematics and Information Science, Guangxi University, Nanning, Guangxi 530004, PR China;2. School of Electrical Engineering, Guangxi University, Nanning, Guangxi 530004, PR China;1. School of Mathematical Sciences, Liaocheng University, Liaocheng, Shandong 252059, PR China;2. School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing 210094, PR China;1. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China;2. School of Automation, Chongqing University, Chongqing 400030, China;1. College of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China;2. CAS Key Laboratory of Planetary Sciences, Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China;3. NARI Group Corporation (State Grid Electric Power Research Institute), Nanjing 211106, China |
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| Abstract: | This paper investigates the event-based state and fault estimation problem for stochastic nonlinear system with Markov packet dropout. By introducing the fictitious noise, the fault is augmented to the system state. Then combining the unscented Kalman filter (UKF) with event-triggered and Markov packet dropout, the modified UKF is proposed to estimate the state and fault. Meanwhile, the stochastic stability of the proposed filter is also discussed. Finally, two simulation results illustrate the performance of the proposed method. |
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