A decentralized adaptive neural controller (DANC) for active vehicle suspension systems using singular perturbation method is developed in this paper. In order to reduce the neural network (NN) weight’s number, the DANC is designed based on the decentralized single input single output (SISO) NN. The active suspension system SIMO characteristic is decoupled into two time-scale separated SISO systems via the singular perturbation technique for achieving a compromise between riding comfort and handing performance. The structure of this MIMO model-free controller is derived from the Lyapunov stability theory to monitor the system for tracking a user-defined reference model. The experimental results are discussed and compared with that of the passive suspension.
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ASME 8th Biennial Conference on Engineering Systems Design and Analysis
July 4–7, 2006
Torino, Italy
ISBN:
0-7918-4250-9
PROCEEDINGS PAPER
A Decentralized Adaptive Neural Controller for Active Vehicle Suspension Systems
Kuo-Ching Chiou,
Kuo-Ching Chiou
National Taiwan University of Science and Technology, Taipei, Taiwan
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Shiuh-Jer Huang
Shiuh-Jer Huang
National Taiwan University of Science and Technology, Taipei, Taiwan
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Kuo-Ching Chiou
National Taiwan University of Science and Technology, Taipei, Taiwan
Shiuh-Jer Huang
National Taiwan University of Science and Technology, Taipei, Taiwan
Paper No:
ESDA2006-95083, pp. 63-68; 6 pages
Published Online:
September 5, 2008
Citation
Chiou, K, & Huang, S. "A Decentralized Adaptive Neural Controller for Active Vehicle Suspension Systems." Proceedings of the ASME 8th Biennial Conference on Engineering Systems Design and Analysis. Volume 3: Dynamic Systems and Controls, Symposium on Design and Analysis of Advanced Structures, and Tribology. Torino, Italy. July 4–7, 2006. pp. 63-68. ASME. https://doi.org/10.1115/ESDA2006-95083
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