Yuexin Pan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Yuexin Pan has a total of 2 co-authors. Here are the top co-authors by number of shared publications:
- Lihong Rong
College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
1 shared publication - Zhimin Tong
College of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, China
1 shared publication
Latest Publications
- Open Access
- 7 May 2025
- Published by MDPI AG in Applied Sciences
- Vol. 15 (9) , 5213
Fault Estimation for Semi-Markov Jump Neural Networks Based on the Extended State Method
This paper addresses fault estimation in discrete-time semi-Markov jump neural networks (s-MJNNs) under the Round-Robin protocol and proposes an innovative extended state observer-based approach. Unlike studies considering only constant transition rates, this work investigates s-MJNNs with time-varying transition probabilities, which more closely reflect practical situations. By incorporating actuator and sensor faults as augmented state variables, an extended state observer is proposed to estimate system states and faults simultaneously. To alleviate network congestion and optimize communication resources, the Round-Robin protocol is adopted to schedule data transmission efficiently. By constructing a Lyapunov–Krasovskii functional and applying the discrete Wirtinger inequality, sufficient conditions are derived to ensure the mean square exponential stability and dissipative performance of the system. The observer gain parameters are computed using the linear matrix inequality (LMI) method. Numerical simulations validate the effectiveness and performance of the proposed fault estimation method.
- 7 May 2025
- Published by MDPI AG in Applied Sciences
- Vol. 15 (9) , 5213
Open AccessFault Estimation for Semi-Markov Jump Neural Networks Based on the Extended State Method
This paper addresses fault estimation in discrete-time semi-Markov jump neural networks (s-MJNNs) under the Round-Robin protocol and proposes an innovative extended state observer-based approach. Unlike studies considering only constant transition rates, this work investigates s-MJNNs with time-varying transition probabilities, which more closely reflect practical situations. By incorporating actuator and sensor faults as augmented state variables, an extended state observer is proposed to estimate system states and faults simultaneously. To alleviate network congestion and optimize communication resources, the Round-Robin protocol is adopted to schedule data transmission efficiently. By constructing a Lyapunov–Krasovskii functional and applying the discrete Wirtinger inequality, sufficient conditions are derived to ensure the mean square exponential stability and dissipative performance of the system. The observer gain parameters are computed using the linear matrix inequality (LMI) method. Numerical simulations validate the effectiveness and performance of the proposed fault estimation method.