DocumentCode
2084651
Title
A discrete-time AILC for systems with non-parametric uncertainties
Author
Chi Ronghu ; Hou Zhongsheng ; Jin Shangtai
Author_Institution
Sch. of Autom. & Electr. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China
fYear
2010
fDate
29-31 July 2010
Firstpage
5877
Lastpage
5882
Abstract
In this paper, a discrete adaptive ILC is presented for a time-varying nonlinear system with nonparametric uncertainties. A novel estimation of nonparametric uncertainties is constructed just using the past I/O data, and the uncertainties are completely compensated such that the output tracking error is only affected by external disturbance. As a main contribution of this paper, all the discussions are done with the random initial condition and the iteration-varying target trajectories. Both the rigorous mathematical analysis and the simulation results illustrate the correctness and effectiveness of the proposed approach.
Keywords
adaptive control; discrete time systems; iterative methods; learning systems; mathematical analysis; parameter estimation; AILC; adaptive iterative learning control; discrete-time system; iteration-varying target trajectory; mathematical analysis; nonlinear system; nonparametric uncertainty estimation; time-varying system; Adaptive control; Artificial neural networks; Bismuth; Target tracking; Trajectory; Uncertainty; Adaptive Iterative learning control; Discrete-time Systems; Iteration-varying Trajectories; Non-parametric Uncertainties; Random Initial Condition;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2010 29th Chinese
Conference_Location
Beijing
Print_ISBN
978-1-4244-6263-6
Type
conf
Filename
5572554
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