journal article·2025-11-27Open access

A Study on Fractional-Order Adaptive Super-Twisting Sliding Mode Control for an Excavator Working Device

Shunjie Zhou, Zhong Liu, Mengyi Li, Deqing Liu, Chongyu Wang, Hao Li

Applied Sciences· Volume 15· Issue 23

Abstract

This study proposes a fractional-order adaptive super-twisting sliding mode control (FO-ASTSMC) strategy to mitigate the difficulties arising from nonlinearity, uncertain parameters, and substantial external interferences during path-following operations of a hydraulic excavator working device. The developed approach merges a high-order sliding mode differentiator aimed at state observation, a fresh fractional-order sliding manifold that embeds a memory component for bolstering transient performance and equilibrium accuracy, together with an adaptable super-twisting coefficient. This adaptive gain eliminates the requirement for prior awareness of disturbance limits, all the while mitigating chattering effects and bolstering system robustness. Utilizing Lyapunov theory, the finite-time stability of the overall closed-loop framework has been thoroughly demonstrated. For controller verification, joint simulations employing AMESim and Simulink platforms were performed, pitting its efficacy against both terminal sliding mode control (TSMC) and adaptive fuzzy sliding mode control (AFSMC). In nominal scenarios, the FO-ASTSMC method yielded the lowest root mean square error (RMSE) along with maximum error (MAXE) across boom, arm, and bucket articulations, registering mean decreases of 60% in RMSE and 58.2% in MAXE when benchmarked against AFSMC, alongside 41.8% in RMSE and 43.6% in MAXE versus TSMC. Facing sudden variations in loading, it exhibited enhanced robustness, achieving reductions of 64.2% in RMSE and 54.5% in MAXE beyond AFSMC, as well as 39% in RMSE and 36.5% in MAXE in comparison to TSMC. Outcomes from the simulations affirm that the suggested controller exhibits elevated precision, formidable robustness, and good applicability to actuators, thereby highlighting its considerable promise for implementation in actual engineering scenarios.
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Research context

OpenAlex topics: Hydraulic and Pneumatic Systems · Vibration Control and Rheological Fluids · Adaptive Control of Nonlinear Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541006, China

Guangxi Key Laboratory of Special Engineering Equipment and Control, Guilin University of Aerospace Technology, Guilin 541004, China

Funding

National Natural Science Foundation of China Grant · Natural Science Foundation of Guangxi Grant

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