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Fixed-structure sampled-data feedforward control for multivariable motion systems
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DOI：10.1016/j.mechatronics.2024.103288.png)
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Abstract
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Increasing performance requirements in high-precision mechatronic systems lead to a situation where both multivariable and sampled-data implementation aspects need to be addressed. The aim of this paper is to develop a design framework fora multi-input multi-output feedforward controller to improve continuous- time tracking performance through learning. The sampled-data feedforward controller is designed with physically interpretable tuning parameters using a multirate zero-order-hold differentiator. The developed approach enables interaction compensation for multi-input multi-output systems and the feedforward controller parameters are updated through learning. The performance improvement is experimentally validated in a multi-input multi-output motion system compared to the conventional feedforward controllers.
Keywords:
Feedforward control
Reference tracking
Multi-input multi-output system
Sampled-data control
Multirate inversion
Iterative learning control
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