A disturbance observer-based adaptive control approach for flexure beam nano manipulators. (January 2016)

• Record Type: Journal Article
• Authors: Zhang, Yangming; Yan, Peng; Zhang, Zhen
• Is Part Of: ISA transactions. Volume 60(2016:Jan.)
• Page Start: 206
• Page End: 217
• Publication Date: 2016-01
• Subjects: Adaptive control -- Disturbance observer -- Tracking control -- Nano servo systems -- Input saturation; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2015.10.005
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This paper presents a systematic modeling and control methodology for a two-dimensional flexure beam-based servo stage supporting micro/nano manipulations. Compared with conventional mechatronic systems, such systems have major control challenges including cross-axis coupling, dynamical uncertainties, as well as input saturations, which may have adverse effects on system performance unless effectively eliminated. A novel disturbance observer-based adaptive backstepping-like control approach is developed for high precision servo manipulation purposes, which effectively accommodates model uncertainties and coupling dynamics. An auxiliary system is also introduced, on top of the proposed control scheme, to compensate the input saturations. The proposed control architecture is deployed on a customized-designed nano manipulating system featured with a flexure beam structure and voice coil actuators (VCA). Real time experiments on various manipulating tasks, such as trajectory/contour tracking, demonstrate precision errors of less than 1%. Abstract : Highlights: The dynamical model of a novel beam flexure-based parallel nano-stage is derived and experimentally determined. A disturbance observer-based adaptive backstepping-like control algorithm is developed where input saturations are also considered by introducing an auxiliary system in the controller structure. The proposed control scheme is successfully implemented in real time on the nano-manipulating system with demonstrated positioning and tracking performance.