Abstract
This paper presents a new design method of semi-active suspensions based on the integration of neural networks and bilinear systems. It is known that semi-active suspensions with ideal linear components have a bilinear structure. However actual semi-active suspensions with nonlinear components have an structure which is not purelv bilinear. In order to improve the performance of semi-active suspensions, neural networks and bilinear systems are integrated and used Tor the identification and optimal control of nonlinear semi-active suspensions. The validity and applicability of the proposed method are analyzed and verified theoretically and experimentally using a semi-active suspension model equipped with piezoelectric actuators.
Original language | English |
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Pages (from-to) | 295-300 |
Number of pages | 6 |
Journal | Journal of Robotics and Mechatronics |
Volume | 7 |
Issue number | 4 |
DOIs | |
State | Published - Aug 1995 |
Externally published | Yes |
Keywords
- Neural networks
- Nonlinear identification
- Nonlinear optimal control
- Ride quality
- Semi-active suspension
- Vibration isolation