Bo Han
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Bo Han has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Chunyan Hu
Key Laboratory of Light-Duty Gas-Turbine, Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
2 shared publications Chunyan Hu
Key Laboratory of Light Duty Gas Turbine, Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing, CHINA
1 shared publicationGang Xu
Key Laboratory of Light Duty Gas Turbine, Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing, CHINA
1 shared publication- Guanzhen Cao
Institute of Engineering Thermophysics Chinese Academy of Sciences, No. 11 North Fourth Ring West Road, Beijing 100190, China
1 shared publication - Hongyang Chen
National Key Laboratory of Science and Technology on Advanced Light-Duty Gas-Turbine, Beijing 100190, China
1 shared publication Jinhu Yang
Key Laboratory of Light Duty Gas Turbine, Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing, CHINA
1 shared publication
Latest Publications
- 27 May 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE/CAA Journal of Automatica Sinica
- Vol. 11 (6) , 1410-1423
Fixed-Time Antidisturbance Consensus Tracking for Nonlinear Multiagent Systems with Matching and Mismatching Disturbances
In this paper, fixed-time consensus tracking for multiagent systems (MASs) with dynamics in the form of strict feedback affine nonlinearity is addressed. A fixed-time antidisturbance consensus tracking protocol is proposed, which consists of a distributed fixed-time observer, a fixed-time disturbance observer, a nonsmooth antidisturbance backstepping controller, and the fixed-time stability analysis is conducted by using the Lyapunov theory correspondingly. This paper includes three main improvements. First, a distributed fixed-time observer is developed for each follower to obtain an estimate of the leader's output by utilizing the topology of the communication network. Second, a fixed-time disturbance observer is given to estimate the lumped disturbances for feedforward compensation. Finally, a nonsmooth antidisturbance backstepping tracking controller with feedforward compensation for lumped disturbances is designed. In order to mitigate the “explosion of complexity” in the traditional backstepping approach, we have implemented a modified nonsmooth command filter to enhance the performance of the closed-loop system. The simulation results show that the proposed method is effective.
- 27 May 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE/CAA Journal of Automatica Sinica
- Vol. 11 (6) , 1410-1423
Fixed-Time Antidisturbance Consensus Tracking for Nonlinear Multiagent Systems with Matching and Mismatching Disturbances
In this paper, fixed-time consensus tracking for multiagent systems (MASs) with dynamics in the form of strict feedback affine nonlinearity is addressed. A fixed-time antidisturbance consensus tracking protocol is proposed, which consists of a distributed fixed-time observer, a fixed-time disturbance observer, a nonsmooth antidisturbance backstepping controller, and the fixed-time stability analysis is conducted by using the Lyapunov theory correspondingly. This paper includes three main improvements. First, a distributed fixed-time observer is developed for each follower to obtain an estimate of the leader's output by utilizing the topology of the communication network. Second, a fixed-time disturbance observer is given to estimate the lumped disturbances for feedforward compensation. Finally, a nonsmooth antidisturbance backstepping tracking controller with feedforward compensation for lumped disturbances is designed. In order to mitigate the “explosion of complexity” in the traditional backstepping approach, we have implemented a modified nonsmooth command filter to enhance the performance of the closed-loop system. The simulation results show that the proposed method is effective.
- Open Access
- 19 March 2024
- Published by MDPI AG in Electronics
- Vol. 13 (6) , 1123
A Method of Diagnosing Analog Circuit Soft Faults Using Boruta Features and LightGBM
Modern electronic power systems rely heavily on analog circuits. The accurate detection of analog circuit faults, especially soft faults, is of great significance for the maintenance and inspection of electronic systems. This paper proposes the application of the Boruta feature selection method to the field of the soft fault diagnosis of analog circuits to screen out low-dimensional and efficient feature components from the high-dimensional time-domain statistical features and frequency-domain features of circuit responses. Then, the feature components are used as the input to train the LightGBM classification model, and the Bayesian optimization method is introduced to optimize the model’s hyperparameters. Finally, the trained fault diagnosis model is verified in two typical experimental circuits, and satisfactory accuracy is obtained.
- 19 March 2024
- Published by MDPI AG in Electronics
- Vol. 13 (6) , 1123
Open AccessA Method of Diagnosing Analog Circuit Soft Faults Using Boruta Features and LightGBM
Modern electronic power systems rely heavily on analog circuits. The accurate detection of analog circuit faults, especially soft faults, is of great significance for the maintenance and inspection of electronic systems. This paper proposes the application of the Boruta feature selection method to the field of the soft fault diagnosis of analog circuits to screen out low-dimensional and efficient feature components from the high-dimensional time-domain statistical features and frequency-domain features of circuit responses. Then, the feature components are used as the input to train the LightGBM classification model, and the Bayesian optimization method is introduced to optimize the model’s hyperparameters. Finally, the trained fault diagnosis model is verified in two typical experimental circuits, and satisfactory accuracy is obtained.
- 7 July 2023
- Published by Springer Nature in Journal of Thermal Science
- Vol. 32 (6) , 2310-2320
A New Methodology for Early Detection of Thermoacoustic Combustion Oscillations Based on Permutation Entropy
- 7 July 2023
- Published by Springer Nature in Journal of Thermal Science
- Vol. 32 (6) , 2310-2320
A New Methodology for Early Detection of Thermoacoustic Combustion Oscillations Based on Permutation Entropy