Paper Info
Title
Decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for a Lorenz chaotic problem
Abstract
This paper introduces a decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for the chaos control problem in a system without precise system model information. It has on-line learning ability to deal with the parametric uncertainty and disturbance by adjusting the control parameters and no constrained conditions and prior knowledge of the controlled plant is required in the design process. Also, a decoupled adaptive sliding mode controller is developed to control the chaotic Lorenz system for comparison. Finally, the effectiveness of the proposed decoupled adaptive sliding mode and DANF sliding mode controllers are demonstrated by some simulated results.
Year
DOI
Venue
2009
10.1016/j.eswa.2008.06.123
Expert Syst. Appl.
Keywords
Field
DocType
anfis,sliding mode,chaotic lorenz system,lorenz,mode control system,simulation,decoupled adaptive,decoupled adaptive neuro-fuzzy,controlled plant,mode controller,chaotic,control parameter,lorenz chaotic problem,chaos control problem,precise system model information,proposed decoupled adaptive,sliding mode control,design process,system modeling,neuro fuzzy
State observer,Neuro-fuzzy,Control theory,Computer science,Control theory,Lorenz system,Parametric statistics,Adaptive neuro fuzzy inference system,Chaotic,Sliding mode control
Journal
Volume
Issue
ISSN
36
3
Expert Systems With Applications
Citations 
PageRank 
References 
12
1.36
2
Authors
2
Name
Order
Citations
PageRank
Ahmad Bagheri1727.64
Jalal Javadi Moghaddam2323.93