Actuator Fault Detection for Unmanned Ground Vehicles Considering Friction Coefficients

This paper proposes an actuator fault detection method for unmanned ground vehicle (UGV) dynamics with four mecanum wheels. The actuator fault detection method is based on unknown input observers for linear parameter varying systems. The technical novelty of current work compared to similar work in the literature is that wheel frictions are directly taken into account in the dynamics of UGV, and unknown input observers are developed accordingly. Including the wheel friction, the vehicle dynamics are in the form of linear parameter varying systems. Friction estimation is also discussed in this work, and the effect of friction mismatch was quantitatively investigated by simulations. The effectiveness of proposed method was evaluated under various operation scenarios of the UGV.

Interval observer-based methodology for passive fault tolerant control of linear parameter-varying systems

The paper deals with passive fault tolerant control for linear parameter varying systems subject to component faults. Under the assumption that the faults magnitudes are considered unknown but bounded, a novel methodology is proposed using interval observer with an [Formula: see text] formalism to attenuate the effects of the uncertainties and to improve the accuracy of the proposed observer. The necessary and sufficient conditions of the control system stability are developed in terms of matrix inequalities constraints using Lyapunov stability theory. Based on a linear state feedback, a fault tolerant control strategy is designed to handle component faults effect as well as external disturbances and preserve the system closed-loop stability for both fault-free and component faulty cases. Two simulation examples are presented to demonstrate the effectiveness of the proposed method.