Neural network based feedback linearization control of a servo-hydraulic vehicle suspension system

@article{Pedro2011NeuralNB,
  title={Neural network based feedback linearization control of a servo-hydraulic vehicle suspension system},
  author={Jimoh Olarewaju Pedro and Olurotimi Akintunde Dahunsi},
  journal={Applied Mathematics and Computer Science},
  year={2011},
  volume={21},
  pages={137-147}
}
This paper presents the design of a neural network based feedback linearization (NNFBL) controller for a two degree-offreedom (DOF), quarter-car, servo-hydraulic vehicle suspension system. The main objective of the direct adaptive NNFBL controller is to improve the system’s ride comfort and handling quality. A feedforward, multi-layer perceptron (MLP) neural network (NN) model that is well suited for control by discrete input-output linearization (NNIOL) is developed using input-output data… CONTINUE READING
Highly Cited
This paper has 25 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 14 extracted citations

Nonlinear feedback linearization controller design for half car suspension system

2013 Annual IEEE India Conference (INDICON) • 2013
View 4 Excerpts
Highly Influenced

References

Publications referenced by this paper.
Showing 1-10 of 69 references

Static output feedback control for electrohydraulic active suspensions via T-S fuzzy model approach

H. Du, N. Zhang
Journal of Dynamic Systems, Measurement and Control: Transactions of ASME • 2009
View 4 Excerpts
Highly Influenced

Multiobjective static output feedback control design for vehicle suspensions

H. Du, N. Zhang
Journal of System Design and Dynamics • 2008
View 7 Excerpts
Highly Influenced

Active suspension design using linear parameter varying control

P. Gaspar, I. Szaszi, J. Bokor
International Journal of Autonomous Systems • 2003
View 4 Excerpts
Highly Influenced

GA - based PID and fuzzy logic control for active vehicle suspension system

J. Z. Feng, J. Li, F. Yu
Inter - national Journal of Automotive Technology • 2003
View 4 Excerpts
Highly Influenced

GA-based PID and fuzzy logic control for active vehicle suspension

J. Z. Feng, J. Li, F. Yu
system, International Journal of Automotive Technology • 2003
View 7 Excerpts
Highly Influenced

Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner’s Handbook

M. Norgaard, O. Ravn, N. K. Poulsen, L. K. Hansen
2003
View 9 Excerpts
Highly Influenced

Road adaptive active suspension design using linear parameter-varying gain-scheduling

IEEE Trans. Contr. Sys. Techn. • 2002
View 4 Excerpts
Highly Influenced

Feedback linearization using neural networks

Automatica • 1995
View 4 Excerpts
Highly Influenced

A new optimal nonlinear approach to half car active suspension control

I. Hassanzadeh, G. Alizadeh, N. P. Shiirjoposht, F. Hashemzadeh
IACSIT International Journal of Engineering and Technology • 2010
View 1 Excerpt

Similar Papers

Loading similar papers…