.png){kind=icon}
Return
Multiple-model adaptive control using set-valued observers
.png){kind=icon}
PRE
AI
DOI：10.1002/rnc.3005.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
A multiple-model adaptive control methodology is proposed that is able to provide stability and performance guarantees, for uncertain linear parameter-varying plants. The identification problem is addressed by taking advantage of recent advances in model falsification using set-valued observers (SVOs). These SVOs provide set-valued estimates of the state of the system, according to its dynamic model. If such estimate is the empty set, the underlying dynamic model is invalidated, and a different controller is connected to the loop. The behavior of the proposed control algorithm is demonstrated in simulation, by resorting to a mass-spring-dashpot system. As a caveat, the computational burden associated with the SVOs can be prohibitive under some circumstances. Copyright (c) 2013 John Wiley & Sons, Ltd.
Keywords:
adaptive control
multiple-model
set-valued observers
uncertain systems
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.2
Papers:
7.0K
Citations:
1.4W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveReaction of some 4-chloro-5-nitropyrimidines with sodium azide. Oxadiazolo[3,4-d]pyrimidine 1-oxides
PREAI
ShareSaveActive mode observation of switching systems based on set-valued estimation of the continuous state
PREAI
ShareSaveShareSave
View more