Please use this identifier to cite or link to this item:
|Title:||On iterative learning control design for tracking iteration-varying trajectories with high-order internal model|
High-order internal model
|Citation:||Yin, C.,Xu, J.,Hou, Z. (2010). On iterative learning control design for tracking iteration-varying trajectories with high-order internal model. Journal of Control Theory and Applications 8 (3) : 309-316. ScholarBank@NUS Repository. https://doi.org/10.1007/s11768-010-0019-6|
|Abstract:||In this paper, iterative learning control (ILC) design is studied for an iteration-varying tracking problem in which reference trajectories are generated by high-order internal models (HOIM). An HOIM formulated as a polynomial operator between consecutive iterations describes the changes of desired trajectories in the iteration domain and makes the iterative learning problem become iteration varying. The classical ILC for tracking iteration-invariant reference trajectories, on the other hand, is a special case of HOIM where the polynomial renders to a unity coefficient or a special first-order internal model. By inserting the HOIM into P-type ILC, the tracking performance along the iteration axis is investigated for a class of continuous-time nonlinear systems. Time-weighted norm method is utilized to guarantee validity of proposed algorithm in a sense of data-driven control. © 2010 South China University of Technology, Academy of Mathematics and Systems Science, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg.|
|Source Title:||Journal of Control Theory and Applications|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 17, 2018
checked on Dec 8, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.