Fixed-Time Adaptive Extended State Observer-Based Enhanced ADRC for Electric Motor Drives
In order to achieve fast convergence of the estimated state and improve the estimation accuracy, a fixed-time adaptive extended state observer (FAESO) is developed for electric motor drives within the active disturbance rejection control (ADRC) framework. First of all, an error adaptive arctangent function is introduced in the design of the FAESO to dynamically improve the lumped disturbance estimation performance of the motor mechanical dynamics. Then, the fixed-time convergence property of the studied FAESO is demonstrated based on the homogeneous theory and Lyapunov function. After the disturbance is estimated quickly and accurately, the error feedback control law is presented to achieve disturbance rejection of the speed loop. The proposed scheme improves the estimation accuracy and convergence rate and enhances the disturbance rejection performance. Finally, the validity and superiority of the proposed FAESO-based enhanced ADRC are verified through three sets of comparative simulation results.
Authors
- Yongting Deng (ORCID: https://orcid.org/0000-0002-3093-6622)
- Yiming Shen (ORCID: https://orcid.org/0000-0003-0227-3857)
- Haiyang Cao (ORCID: https://orcid.org/0000-0001-6879-3068)
- Christopher H. T. Lee (ORCID: https://orcid.org/0000-0001-5132-4126)
- Xiufeng Liu (ORCID: https://orcid.org/0000-0002-0193-6121)
- Yang Liu (ORCID: https://orcid.org/0009-0004-3247-1525)
Institutions
- Nanyang Technological University (SG)
- Changchun Institute of Optics, Fine Mechanics and Physics (CN)
Publication Details
- Journal
- IEEE Transactions on Circuits & Systems II Express Briefs
- Published
- 2025-03-07
- DOI
- https://doi.org/10.1109/tcsii.2025.3549070
- Citations
- 2
- Primary Topic
- Iterative Learning Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 2.43
Funders
- National Natural Science Foundation of China
- Youth Innovation Promotion Association of the Chinese Academy of Sciences
- Jilin Province Key R&D Plan Project