Parameter Identification of LuGre Tire Model for the Simplified Motion Dynamics of a Quarter-vehicle Model Based on Ant Colony Algorithm
In light of the high nonlinearity of LuGre friction model, a novel method based on ant colony algorithm (ACA) for identifying the friction parameters of LuGre tire model is proposed. ACA is a parallelized bionic optimization algorithm inspired from the behavior of real ants, and a kind of positive feedback mechanism is adopted in ACA. On the basis of brief introduction of LuGre friction model, a method for identifying the static LuGre friction parameters and the dynamic LuGre friction parameters using ACA is derived. Finally, this new friction parameter identification scheme is applied to the simplified motion dynamics of a quarter-vehicle model with high precision. Simulation and application results verify the feasibility and the effectiveness of the scheme. It provides a new way to identify the friction parameters of LuGre tire model.
parameter identification LuGre tire model ACA friction
Jiapeng Han Yongli Sun Yanyang Wang
School of Transportation and Vehicle Engineering Shandong University of Technology Zibo, Shandong Province,China
国际会议
2007 IEEE International Conference on Automation and Lofistics
山东济南
英文
2007-08-18（万方平台首次上网日期，不代表论文的发表时间）