Title :
On-line adaptive T-S fuzzy neural control for active suspension systems
Author :
Wang, Wei-Yen ; Chen, Ming-Chang ; Chien, Yi-Hsing ; Lee, Tsu-Tian
Author_Institution :
Dept. of Appl. Electron. Technol., Nat. Taiwan Normal Univ., Taipei, Taiwan
Abstract :
Vehicles are not always driven on smooth roads. If parts of the suspension system fail, it becomes an uncertain system. Thus we need an approximator to remodel this uncertain system to maintain good control. In this paper, we propose a new method to on-line identify the uncertain suspension system and design a T-S fuzzy-neural controller to control it. We first use the mean value theorem to transform the active suspension system into a virtual linearized system. In addition, an on-line adaptive T-S fuzzy-neural modeling approach to the design of robust tracking controllers is developed for the uncertain active suspension system. Finally, this paper gives simulation results of an uncertain suspension system with the on-line adaptive T-S fuzzy-neural controller, and is shown to provide good effectiveness under the conditions that parts of the suspension system fail.
Keywords :
adaptive control; control system synthesis; fuzzy control; linearisation techniques; neurocontrollers; road vehicles; robust control; suspensions (mechanical components); uncertain systems; vehicle dynamics; mean value theorem; online adaptive T-S fuzzy neural control design; robust tracking controller; uncertain active vehicle suspension system; virtual linearized system; Adaptive control; Control systems; Fuzzy control; Fuzzy systems; Programmable control; Road vehicles; Robust control; Uncertain systems; Vehicle driving; Vehicle safety;
Conference_Titel :
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location :
Jeju Island
Print_ISBN :
978-1-4244-3596-8
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2009.5277406