Title: Study on soft computing arithmetic for vehicle yaw rate based on ANFIS

Authors: Jianwei Wei; Minxiang Wei; Wanzhong Zhao

Addresses: Department of Automotive Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. ' Department of Automotive Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China. ' Department of Automotive Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Abstract: A soft computing arithmetic based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed to estimate vehicle yaw rate in a driver-vehicle closed loop system, and vehicle yaw rate is considered as a nonlinear mapping of time series of rack displacement and lateral acceleration. Simulation study on soft computing of vehicle yaw rate in the driver-vehicle closed loop system is conducted, and the performance of the soft computing arithmetic based on ANFIS is evaluated with the help of actual vehicle test data. Results indicate that the generalisation of the soft computing arithmetic based on ANFIS is better than that based on Radial Basis Function (RBF) neural network.

Keywords: vehicle yaw rate; soft computing; driver-vehicle closed loop systems; ANFIS; adaptive neuro-fuzzy inference system; RBF; radial basis function; neural networks; fuzzy logic; simulation.

DOI: 10.1504/IJVD.2011.043274

International Journal of Vehicle Design, 2011 Vol.56 No.1/2/3/4, pp.146 - 160

Received: 17 May 2010
Accepted: 21 Jan 2011
Published online: 10 Apr 2015 *

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