Paper Info
Title
ILC for networked nonlinear systems with unknown control direction through random Lossy channel.
Abstract
The iterative learning control is constructed for the discrete-time networked nonlinear systems with random measurement losses and unknown control direction, which have not been studied simultaneously in literature. Differing from the conventional Bernoulli random variable model, the random packet loss is modeled by an arbitrary stochastic sequence with bounded length requirement, which is a new model of realistic packet losses. A novel regulating approach based on truncations is introduced to make the proposed algorithm find the correct control direction adaptively, and then guarantee the almost sure convergence property. Therefore, this paper has three major innovations compared with reported studies, namely, the stochastic sequence model of packet loss, the novel control direction regulation method, and the almost sure convergence property of the proposed algorithm. An illustrative example shows the effectiveness of the proposed approach.
Year
DOI
Venue
2015
10.1016/j.sysconle.2014.12.008
Systems & Control Letters
Keywords
Field
DocType
Iterative learning control,Networked control system,Random packet losses,Stochastic approximation
Bernoulli distribution,Convergence of random variables,Mathematical optimization,Nonlinear system,Control theory,Networked control system,Packet loss,Iterative learning control,Stochastic approximation,Mathematics,Bounded function
Journal
Volume
ISSN
Citations 
77
0167-6911
8
PageRank 
References 
Authors
0.60
8
2
Name
Order
Citations
PageRank
Dong Shen115517.64
Youqing Wang222025.81