Title
Data-Driven Control For Feedback Linearizable Single-Input Systems
Abstract
More than a decade ago Fliess and co-workers [1], [2], [3] proposed model-free control as a possible answer to the inherent difficulties in controlling non-linear systems. Their key insight was that by using a sufficiently high sampling rate we can use a simple linear model for control purposes thereby trivializing controller design. In this paper, we provide a variation of model-free control for which it is possible to formally prove the existence of a sufficiently high sampling rate ensuring that controllers solving output regulation and tracking problems for the approximate linear model also solve the same problems for the true and unknown nonlinear model. This is verified experimentally on the bipedal robot AMBER-3M.
Year
Venue
Field
2017
2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC)
Nonlinear system,Data-driven,Controller design,Computer science,Linear model,Control theory,Sampling (signal processing),Vehicle dynamics,Control system,Robot
DocType
ISSN
Citations 
Conference
0743-1546
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Paulo Tabuada14281264.80
Wen-Loong Ma2256.05
J. w. Grizzle32188215.15
Aaron D. Ames41202136.68