2003
DOI: 10.1006/jsvi.2002.5136
|View full text |Cite
|
Sign up to set email alerts
|

A Stochastic Optimal Semi-Active Control Strategy for Er/MR Dampers

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
46
0

Year Published

2007
2007
2020
2020

Publication Types

Select...
9

Relationship

0
9

Authors

Journals

citations
Cited by 93 publications
(46 citation statements)
references
References 21 publications
0
46
0
Order By: Relevance
“…(9) shows the linearization of nonlinear saturation, c is the controllable yield damping force of the damper. The mathematical expression is: …”
Section: Model and Analysis Of Double-layer Vibration Suppression Bilmentioning
confidence: 99%
See 1 more Smart Citation
“…(9) shows the linearization of nonlinear saturation, c is the controllable yield damping force of the damper. The mathematical expression is: …”
Section: Model and Analysis Of Double-layer Vibration Suppression Bilmentioning
confidence: 99%
“…The application ranges of these vibration reduction systems are very wide such as it is applied to submarine floating raft isolation systems [4], used in vibration reduction systems of vehicle suspensions [5,6], etc. There are three main types of vibration suppression methods that have been proposed in the same way as the classification of the vibration control, that is passive method [7], semi-active method [8][9][10], and active method.…”
Section: Introductionmentioning
confidence: 99%
“…A dynamic programming equation to constrain ER/MR damping forces is used to determine the optimal control law effectiveness of the proposed controller. The effectiveness of the controller is illustrated in two examples [6]. El-Kafafy et al studied a quarter vehicle model with two DOFs incorporating an MR damper.…”
Section: Introductionmentioning
confidence: 99%
“…However, the linear-quadratic-Gauss (LQG) control method has mostly used for structural vibration control [5]. Recently, some stochastic optimal nonlinear control methods [6,7] have been proposed, in particular, the method based on the stochastic dynamical programming principle and stochastic averaging method [8][9][10][11][12][13][14][15][16][17]. This control method can achieve better control effectiveness and efficiency than the LQG control method.…”
Section: Introductionmentioning
confidence: 99%