Title
Concurrent Learning-Based Global Exponential Tracking Control of Uncertain Switched Systems With Mode-Dependent Average Dwell Time.
Abstract
This paper investigates the problem of global exponential tracking control for switched nonlinear systems with linear uncertain parameters and without persistency of excitation. A switched model reference adaptive control technique, using the mode-dependent average dwell time method and a concurrent learning approach, is proposed for the first time. A sufficient condition is provided to ensure that the dynamics of the state tracking error and the adaptive weight error converge to zero exponentially rapidly. Consequently, the relationship among the average dwell time of each subsystem, the concurrent learning algorithm, and the performance of uncertain switched systems is established. Furthermore, the transient performance bounds of the state tracking error and the adaptive weight error are studied. Finally, an illustrative numerical example is provided to demonstrate the effectiveness of the proposed method.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2854720
IEEE ACCESS
Keywords
Field
DocType
Switched systems,concurrent learning,mode-dependent average dwell time,model reference adaptive control
Convergence (routing),Dwell time,Nonlinear system,Exponential function,Computer science,Adaptive system,Control theory,Adaptive control,Distributed computing,Exponential growth,Tracking error
Journal
Volume
ISSN
Citations 
6
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Caiyun Wu1168.46
Xiaoping Huang201.69
Ben Niu300.34
xuejun xie41087.81