Non-linear Observer for Slip Parameter Estimation of Unmanned Wheeled Vehicles

This paper presents a non-linear sliding mode observer (SMO) for the estimation of wheeled vehicle slip parameters based on the vehicle kinematic model and on-board sensor inputs. Lyapunov stability theory is used to establish the stability conditions for the observer. It is shown that the observer will converge in a finite time, provided the observer gains satisfy constraints based on the stability analysis. Since vehicle position and velocity can not be very accurately measured using on-board sensors, specially designed linear and 2D test rigs are used to validate the proposed observer. The SMO is tested under a variety of conditions and it is shown that the SMO can estimate the slip parameters to a high accuracy. It is also shown that the SMO can accurately predict the slip parameters in the presence of noise by testing the SMO after adding white noise to the measurements. An extended Kalman filter is presented for the purpose of comparison. Thus the proposed observer has the potential to be used on unmanned ground vehicles equipped with sensing systems such as GPS or inertial sensors.