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Novel multi-square-pulse compensation algorithm for reducing quadrant protrusion by injecting signal with optimal waveform.

Authors :
Liu, Chung-Ching
Tsai, Meng-Shiun
Lin, Ming-Tsung
Tang, Pu-Yang
Source :
Mechanism & Machine Theory. Aug2020, Vol. 150, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

• The novel servo-friction model is developed for predicting the quadrant protrusions. • The factors of quadrant protrusions under different motion conditions are analyzed. • The optimization to determine the quadrant error compensation parameters is proposed. • A new multi-square-pulse compensation method and its tuning algorithm are suggested. • The experimental results compensated by different approaches are discussed. The nonlinear phenomenon of friction causes significant tracking errors when a platform reverses its moving direction. These tracking errors can cause quadrant protrusion (QP) for circular motion. To solve this problem, the conventional approach is to inject a compensation signal during the period of velocity reversal to overcome the friction effect. The waveform of this compensation signal has not yet been investigated. In this paper, a novel multi-square-pulse compensation (MSPC) method is proposed based on minimization of QP to determine the optimal MSPC waveform. To implement MSPC, the waveform is first computed using an identified servo-friction model. MSPC signals for the trajectories with different velocities and accelerations (Vel/Acc) are discussed, and the performance is compared with that of conventional quadrant error compensation (QEC). To validate the novel MSPC algorithm, experiments were conducted on an XY table. To further improve the experimental results by considering modeling errors, MSPC incorporating a tuning algorithm, called MSPC_TA, is proposed. The experimental results with different Vel/Acc show that QPs can be reduced by 95% by using the MSPC_TA approach. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094114X
Volume :
150
Database :
Academic Search Index
Journal :
Mechanism & Machine Theory
Publication Type :
Academic Journal
Accession number :
142912767
Full Text :
https://doi.org/10.1016/j.mechmachtheory.2020.103875