Adaptive Sliding Mode Control Based on a Peak-Suppression Extended State Observer for Angle Tracking in Steer-by-Wire Systems

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Authors: Guoqing Geng, Debang Sun, Jiantao Ma, Haoran Li
Cited by: 1
References: 38

Abstract

To address the degradation of angle tracking performance in steer-by-wire (SBW) systems caused by external disturbances and parameter uncertainties, this paper proposes a composite control strategy integrating adaptive sliding mode control (ASMC) and a peak-suppression extended state observer (PSESO). Firstly, a novel sliding mode reaching law is designed, which incorporates a dynamic adaptive gain function to achieve real-time adjustment of the control gain. This approach accelerates the reaching speed while effectively mitigating chattering. Secondly, to enhance the disturbance rejection capability of the system, a PSESO is developed to estimate the lumped disturbance in the SBW system in real time. By dynamically adjusting the observer bandwidth, the peak phenomenon in state estimation is suppressed, thereby avoiding saturation of the control signal. The disturbance estimate from the PSESO is then fed forward as a compensation term into the adaptive sliding mode (ASM) controller, forming a composite ASMC+PSESO controller that enables active compensation and suppression of disturbances. Finally, the proposed composite control strategy is validated through both simulations and experiments. Experimental results demonstrate that under sinusoidal signal tracking conditions, the proposed method reduces the maximum tracking error, the mean absolute error, and the integral absolute error by 64.4%, 74.2%, and 73.1%, respectively, compared to traditional sliding mode control (TSMC). These results fully underscore its superiority in angle tracking control and disturbance rejection for SBW systems.

Fields of Study & Subjects

Adaptive Control of Nonlinear Systems Iterative Learning Control Systems Hydraulic and Pneumatic Systems

Publication details

Journal / source
Actuators
Publisher
MDPI AG
Volume
15
Issue
2
Pages
128–128
Publication date
19 February 2026
Language
EN