TY - GEN
T1 - Control of uncertain active suspension system with anti-lock braking system using fuzzy neural controllers
AU - Wang, Wei Yen
AU - Chien, Yi Hsing
AU - Chen, Ming Chang
AU - Lee, Tsu Tian
PY - 2009
Y1 - 2009
N2 - This paper proposes anti-lock braking system to integrate with active suspensions system applied in a quarter vehicles model, and can use a road estimate to get the road condition. This estimate is based on the LuGre friction model with a road condition parameter, and can transmit a reference slip ration to slip ratio controller through a mapping function considering the effect of road characteristics. In the controller design, an observer-based direct adaptive fuzzy-neural controller (DAFC) for an ABS is developed. After, this paper will discuss that active suspension system influence on ABS. Active suspension systems are not ideal, unchanging, and certain, as many control systems assume. If parts of the suspension system fail, it becomes an uncertain system. In such cases, we need an approximator to remodel this uncertain system to maintain good control. We propose a new method to on-line identify the uncertain active suspension system and design a T-S fuzzy-neural controller to control it. Finally, integrating algorithm is constructed to coordinate these two subsystems. Simulation results of the ABS with active suspension system, and is shown to provide good effectiveness under varying conditions.
AB - This paper proposes anti-lock braking system to integrate with active suspensions system applied in a quarter vehicles model, and can use a road estimate to get the road condition. This estimate is based on the LuGre friction model with a road condition parameter, and can transmit a reference slip ration to slip ratio controller through a mapping function considering the effect of road characteristics. In the controller design, an observer-based direct adaptive fuzzy-neural controller (DAFC) for an ABS is developed. After, this paper will discuss that active suspension system influence on ABS. Active suspension systems are not ideal, unchanging, and certain, as many control systems assume. If parts of the suspension system fail, it becomes an uncertain system. In such cases, we need an approximator to remodel this uncertain system to maintain good control. We propose a new method to on-line identify the uncertain active suspension system and design a T-S fuzzy-neural controller to control it. Finally, integrating algorithm is constructed to coordinate these two subsystems. Simulation results of the ABS with active suspension system, and is shown to provide good effectiveness under varying conditions.
KW - Active suspension system
KW - Anti-lock braking system
KW - DAFC
KW - T-S fuzzy-neural
UR - http://www.scopus.com/inward/record.url?scp=74849083083&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=74849083083&partnerID=8YFLogxK
U2 - 10.1109/ICSMC.2009.5346194
DO - 10.1109/ICSMC.2009.5346194
M3 - Conference contribution
AN - SCOPUS:74849083083
SN - 9781424427949
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 3371
EP - 3376
BT - Proceedings 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009
T2 - 2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009
Y2 - 11 October 2009 through 14 October 2009
ER -