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.
Published Version
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