Event-triggered sampled-data iterative learning control for parabolic distributed parameter systems with polynomial growth
DAI Xi-sheng
HE Jun
ZHOU Ru-sheng
Abstract：For the output trajectory tracking problem of nonlinear parabolic distributed parameter systems with poly-nomial growth,an sampled-data iterative learning control method based on event-triggered strategy is proposed.Firstly,the polynomial term is analyzed using Young's inequality,and a constraint inequality about the polynomial function is obtained.Then,a mixed event-triggered condition with a trigger strength factor is designed based on the Lyapunov-like method and the threshold trigger mechanism,and the corresponding P-type event-triggered sampled-data iterative learning control algorithm is given.The convergence of the output error at the sampling instant is analyzed by using the compression mapping principle,and a sufficient condition is established for the output error at the sampling instant to converge to zero along the iterative direction.Finally,the flow of the control algorithm is given,and the effectiveness of the algorithm given in this paper is verified by numerical simulation.
Keywords：iterative learning controlsampled-dataevent-triggeredpolynomial growthdistributed parameter systems
Publication Date：2025-07-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 1435-1442 )