Unknown dynamics estimator-based output-feedback control for nonlinear pure-feedback systems

Na, Jing; Yang, Jun; Wang, Shubo; Gao, Guanbin; Yang, Chenguang

Abstract

Most existing adaptive control designs for nonlinear pure-feedback systems have been derived based on backstepping or dynamic surface control (DSC) methods, requiring full system states to be measurable. The neural networks (NNs) or fuzzy logic systems (FLSs) used to accommodate uncertainties also impose demanding computational cost and sluggish convergence. To address these issues, this paper proposes a new output-feedback control for uncertain pure-feedback systems without using backstepping and function approximator. A coordinate transform is first used to represent the pure-feedback system in a canonical form to evade using the backstepping or DSC scheme. Then the Levant's differentiator is used to reconstruct the unknown states of the derived canonical system. Finally, a new unknown system dynamics estimator with only one tuning parameter is developed to compensate for the lumped unknown dynamics in the feedback control. This leads to an alternative, simple approximation-free control method for pure-feedback systems, where only the system output needs to be measured. The stability of the closed-loop control system, including the unknown dynamics estimator and the feedback control is proved. Comparative simulations and experiments based on a PMSM test-rig are carried out to test and validate the effectiveness of the proposed method.

Citation

Na, J., Yang, J., Wang, S., Gao, G., & Yang, C. (2021). Unknown dynamics estimator-based output-feedback control for nonlinear pure-feedback systems. IEEE Transactions on Systems Man and Cybernetics: Systems, 51(6), 3832-3843. https://doi.org/10.1109/tsmc.2019.2931627

• Journal Article Type: Article
• Acceptance Date: Jul 19, 2019
• Online Publication Date: Aug 20, 2019
• Publication Date: Jun 1, 2021
• Deposit Date: Aug 27, 2019
• Publicly Available Date: Aug 27, 2019
• Journal: IEEE Transactions on Systems, Man, and Cybernetics: Systems
• Print ISSN: 2168-2216
• Electronic ISSN: 2168-2232
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 51
• Issue: 6
• Pages: 3832-3843
• DOI: https://doi.org/10.1109/tsmc.2019.2931627
• Keywords: Control and Systems Engineering; Human-Computer Interaction; Electrical and Electronic Engineering; Software; Computer Science Applications
• Public URL: https://uwe-repository.worktribe.com/output/2489319
• Publisher URL: https://ieeexplore.ieee.org/document/8807384