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Abstract and Applied Analysis
Volume 2014, Article ID 765871, 6 pages
http://dx.doi.org/10.1155/2014/765871
Research Article

Nonlinear Time-Delay Suspension Adaptive Neural Network Active Control

College of Engineering, Nanjing Agricultural University, Nanjing 210031, China

Received 2 July 2014; Accepted 15 August 2014; Published 27 August 2014

Academic Editor: Zheng-Guang Wu

Copyright © 2014 Yue Zhu and Sihong Zhu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Considering the time-delay in control input channel and the nonlinear spring stiffness characteristics of suspension, a quarter-vehicle magneto rheological active suspension nonlinear model with time-delay is established in this paper. Based on the time-delay nonlinear model, an adaptive neural network structure for magneto rheological active suspension is presented. By recognizing and training the adaptive neural network, the adaptive neural network active suspension controller is obtained. Simulation results show that the presented method can guarantee that the quarter-vehicle magneto rheological active suspension system has satisfying performance on the E_level very poor ground.