Journal
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
Volume 49, Issue 4, Pages 687-696Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2017.2693397
Keywords
Additional control inputs; data-driven control; experimental verification; nonlinear discrete-time systems; pointto-point iterative learning control (PTPILC)
Funding
- National Science Foundation of China [61374102, 61433002, 61120106009]
- Taishan Scholar Program of Shandong Province of China
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In this paper, an improved data-driven point-to-point iterative learning control is proposed for nonlinear repetitive systems where only the system outputs at the multiple intermediate prespecified points are considered. The entire finite time interval is divided into multiple time-subintervals according to the prespecified points. Then a new objective function is designed to generate optimal control inputs over a time-subinterval piecewisely. As a result, the control inputs are updated in a time-subinterval wise using additional input signals from the previous time-subintervals of the same iteration to help improving control performance. By removing the constraints on the unimportant intermediate points, the control system can be designed with additional freedom to achieve a better performance in tracking points of interest. Meanwhile, the proposed approach is data-driven and no process model is required for the control system design and analysis. Both a simulation with nonlinear batch reactor and an experiment with a permanent magnet linear motor servomechanism are provided to demonstrate the effectiveness of the proposed method.
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