Please use this identifier to cite or link to this item:
https://doi.org/10.1109/ACCESS.2019.2950211
Title: | Adaptive Robust Control Based on Moore-Penrose Generalized Inverse for Underactuated Mechanical Systems | Authors: | Chen, X. Zhao, H. Sun, H. Zhen, S. |
Keywords: | adaptive law adaptive robust control Moore-Penrose generalized inverse servo constraints Underactuated mechanical systems |
Issue Date: | 2019 | Publisher: | Institute of Electrical and Electronics Engineers Inc. | Citation: | Chen, X., Zhao, H., Sun, H., Zhen, S. (2019). Adaptive Robust Control Based on Moore-Penrose Generalized Inverse for Underactuated Mechanical Systems. IEEE Access 7 : 157136-157144. ScholarBank@NUS Repository. https://doi.org/10.1109/ACCESS.2019.2950211 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International | Abstract: | To address the uncertainty existing in underactuated mechanical systems (UMSs) and their nonholonomic servo constraints, we propose a class of adaptive robust control based on the Moore-Penrose generalized inverse for UMSs in this paper. The uncertainty is considered as (possible fast) time-varying and bounded. However, the bound is unknown. To estimate the bound information, an adaptive law is designed, which combines leakage type and dead-zone type. This adaptive law can simultaneously regulate the control effort and computation speed. The proposed control can guarantee deterministic system performance, which is analyzed by using Lyapunov method. The effectiveness of proposed control is shown by an example of simplified two-wheeled self-balancing robot. © 2013 IEEE. | Source Title: | IEEE Access | URI: | https://scholarbank.nus.edu.sg/handle/10635/212617 | ISSN: | 21693536 | DOI: | 10.1109/ACCESS.2019.2950211 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International |
Appears in Collections: | Staff Publications Elements |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
10_1109_ACCESS_2019_2950211.pdf | 6.69 MB | Adobe PDF | OPEN | None | View/Download |
This item is licensed under a Creative Commons License