Name
Abstract | ||
|---|---|---|
Repetitive control enables the exact compensation of periodic disturbances if the internal model is appropriately selected. The aim of this paper is to develop a novel synthesis technique for repetitive control (RC) based on a new more general internal model. By employing a Gaussian process internal model, asymptotic rejection is obtained for a wide range of disturbances through an appropriate selection of a kernel. The implementation is a simple linear time-invariant (LTI) filter that is automatically synthesized through this kernel. The result is a user-friendly design approach based on a limited number of intuitive design variables, such as smoothness and periodicity. The approach naturally extends to reject multi-period and non-periodic disturbances, exiting approaches are recovered as special cases, and a case study shows that it outperforms traditional RC in both convergence speed and steady-state error. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.automatica.2022.110273 | Automatica |
Keywords | DocType | Volume |
Repetitive control,Gaussian processes,Internal model control,Disturbance rejection | Journal | 140 |
ISSN | Citations | PageRank |
0005-1098 | 1 | 0.37 |
References | Authors | |
0 | 3 | |