This paper investigates the steering fault detection problem for autonomous ground vehicles (AGVs). Using an observer-based approach, a new fuzzy fault detector for steering actuator is designed for safety concern. To this end, a two degrees-of-freedom (2-DOF) nonlinear vehicle model is adopted to represent the nonlinear dynamics of AGVs. Since it is not easy to measure the lateral velocity in practice, this model is then represented in a specific Takagi-Sugeno (TS) fuzzy form with nonlinear consequents. In contrast to the conventional TS fuzzy modeling, it allows separating the unmeasured premise variables in the local nonlinear consequent, which enables a more effective way to deal with the challenging issue of unmeasured premise variables. Moreover, to minimize the effect of disturbances on system performance and maximize that of actuator faults on the generated residual, both H∞ disturbance attenuation index and H− fault sensitivity index are taken into account in a finite-frequency domain. The conditions to design fault detection TS fuzzy observer are derived using Lyapunov stability method. The design procedure can be reformulated as an optimization problem under linear matrix inequalities, efficiently solved by standard numerical solvers. Simulation results are given to verify the fault detection performance of the proposed method.