Comparative Study of Performance-Oriented Feedforward Compensation Strategies for Precision Mechatronic Motion Systems
Ran Zhou, Chuxiong Hu, Bingyang Hou and 1 more
IEEE Access · 2022
doi:10.1109/access.2022.3207162 (opens in a new tab)
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Abstract
To meet the progressively stringent demands for trajectory tracking performance in precision/ ultra-precision industry, multiple advanced feedforward compensation strategies have been reported in recent years. However, there is no fair and comprehensive performance comparison of advantages and drawbacks of various methods under different industrial working conditions. In this paper, a comparative study of several performance-oriented feedforward strategies represented by standard iterative learning control (ILC), cascaded ILC (CILC), gated recurrent units based feedforward compensation (GRU-FFC), and real-time iterative compensation (RIC) has been systematically conducted by theoretical clarification and experimental verification. Various trajectory tracking tasks are accomplished on a precision mechatronic motion stage, and the tracking performances to be examined include (i) tracking accuracy; (ii) extrapolation capability for non-repetitive trajectories; (iii) disturbance rejection ability. Experimental results are sufficiently summarized with the combination of underlying control mechanism analysis, which can provide a comprehensive and reliable selection guidance of feedforward compensation strategies in different practical industrial scenarios.
Abstract licence: CC BY-NC-ND
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