Paper Info
Title
Fuzzy cerebellar model articulation controller (FCMAC) for vibration control on ocean engineering vehicles
Abstract
In this paper, it was studied the semi-active quarter-coach suspension based on ocean engineering vehicles. The physical model of semi-active quarter-coach suspension was established based on the theories of Buckingham's Pi theorem. According to the characteristics of the semi-active suspension, a new intelligent control algorithm based on the Fuzzy logic control and cerebellar model articulation control techniques-Fuzzy cerebellar model articulation control (FCMAC) was presented and used to perform online control of semi-active suspension for the first time, novel weight-update laws were derived that guarantee the stability of closed-loop system, both information retrieval and learning rules were described by algebraic equations in matrix form. The results of experiment of closed-loop excited by three typical vibration signals showed that FCMAC control strategy can reduce the value of mean square root of vertical acceleration of semi-active suspension system to be lower 23%, 25% and 18% compared with the traditional control strategy such as PID.
Year
DOI
Venue
2010
10.1109/ICNC.2010.5583835
ICNC
Keywords
Field
DocType
algebraic equations,buckingham pi theorem,intelligent control algorithm,fcmac,intelligent control,learning rules,ocean engineering vehicles,learning (artificial intelligence),semi-active suspension,information retrieval,vehicles,pid,fuzzy cerebellar model articulation controller,closed-loop system,mean square root,physical model,ocean engineering vehicle,fuzzy logic control,matrix form,fuzzy control,vibration control,stability,closed loop systems,semiactive quarter-coach suspension,brain models,three-term control,servomotors,learning artificial intelligence,valves,mathematical model
Intelligent control,Suspension (vehicle),Vibration control,PID controller,Computer science,Control theory,Algebraic equation,Buckingham π theorem,Fuzzy control system,Marine engineering,Servomotor
Conference
Volume
ISBN
Citations 
1
978-1-4244-5958-2
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Shiming Wang112.40
Aiping Wu200.34