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Electric power steering control faces several issues related to state errors, sensor noise, and chattering. This article proposes an adaptive robust control method based on a sliding mode control mechanism to address the existing drawbacks. The sliding surface of this controller is adjusted dynamically by a fuzzy technique, which is formed by two inputs and one output. The system disturbances and state variables are estimated by an extended state observer instead of being measured by expensive sensors. Combining the above techniques is a new contribution to the article to improve the system’s control performance. Numerical simulations are performed in three cases with varying driver torque and velocity. The computational results reveal that the output signals of the system controlled by the proposed method closely track the desired values, with errors not exceeding 1.5% (except for the assisted current). The observed error of the system disturbance does not exceed 12.172%, while the observed error of the remaining state variables is less than 3%. Overall, the performance of the proposed algorithm is significantly improved compared with the traditional control methods.
