Active disturbance rejection control for nanopositioning: A robust U-model approach. (September 2022)

• Record Type: Journal Article
• Authors: Wei, Wei; Duan, Bowen; Zhang, Weicun; Zuo, Min
• Is Part Of: ISA transactions. Volume 128(2022)Part B
• Page Start: 599
• Page End: 610
• Publication Date: 2022-09
• Subjects: Piezoelectric actuator -- Nanopositioning -- Hysteresis -- LADRC -- U-model control; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2021.11.035
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: Hysteresis severely reduces positioning performance of a piezoelectric nanopositioning stage. Linear active disturbance rejection control (LADRC) is a practical solution to improve the positioning accuracy. However, the PD controller utilized in the LADRC is not effective enough to suppress the uncancelled total disturbance, and high-order pure integrators are difficult to be stabilized just by a PD controller. In this work, a robust U-model active disturbance rejection control (RUADRC) is proposed by incorporating the core idea of the U-model control and the Glover–McFarlane control. Then, the controlled plant can be dynamically transformed to a unit. Difficulties in stabilizing high-order pure integrators are decreased, the phase lag between the input and output of a controlled plant is reduced, and the closed-loop responses is sped up. In addition, the influence of both inaccurate total disturbance estimation and imperfect approximation is also minimized by the Glover–McFarlane control Closed-loop stability, steady-state tracking error, and the phase advantage of the RUADRC have been analysed. Theoretical results show that the RUADRC promises a timelier and more accurate positioning. Experimental results still confirm the advantages of the RUADRC over the LADRC on both reference tracking speed, accuracy and disturbance rejection ability. Highlights: A robust U-model active disturbance rejection control is proposed to realize a high performance and more robust positioning. An inverse model of a positioning stage is obtained skilfully by incorporating an extended state observer, and the UC becomes more adaptive. A more practical approach has been provided to utilize the elegant Glover–McFarlane control.