Integration of Bilinear Systems and Neural Networks for Designing Nonlinear Semi-Active Suspensions | Zendy

Antonio Morán | Zendy; Tomohiro Hasegawa | Zendy; Masao NAGAI | Zendy

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Integration of Bilinear Systems and Neural Networks for Designing Nonlinear Semi-Active Suspensions

Author(s) -

Antonio Morán,

Tomohiro Hasegawa,

Masao NAGAI

Publication year - 1995

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.1995.p0295

Subject(s) - active suspension , bilinear interpolation , nonlinear system , control theory (sociology) , artificial neural network , computer science , actuator , control engineering , engineering , artificial intelligence , control (management) , physics , quantum mechanics , computer vision

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 purely bilinear. In order to improve the performance of semi-active suspensions, neural networks and bilinear systems are integrated and used for 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.

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