On adaptive iterative learning control:the state of the art and perspective
LI Xue-fang
LI Xiao-dong
LIU Wan-quan
Abstract：This work reviews the state of the art in the area of adaptive iterative learning control(AILC)targeting at different problems,in which some possible future research directions are also presented.First of all,we present a brief overview on the analysis tool and design frameworks of AILC.Then,the latest developments in AILC field are discussed from both the aspects of system structure characteristics and operation characteristics,including the issues on non-parametric uncertainties,input nonlinearities/uncertainties,constrained systems,unmeasurable states,non-repeatable factors,etc.For each type of these issues,the characteristics on design and analysis of the controller are presented in details.Furthermore,the design principles of data-driven AILC are discussed.Finally,we summarize some open and challenging issues in AILC,which need to be further explored and investigated.
Keywords：iterative learning controladaptive iterative learning controldata-drivennonlinear systemscomposite energy function
Publication Date：2024-09-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：16( 1523-1538 )