Balanced Walking Force Control for Walking Excavators Based on Dual Strong Tracking Kalman Filter

The operation of walking excavators on rugged terrain often leads to leg lift-off, which can result in uneven force distribution, accelerated structural wear, and even systemic instability. To address these issues, this paper proposes a coordinated control framework comprising three integral components: a Dual Strong Tracking Kalman Filter (DSTKF) for estimating unmeasurable system states—such as joint velocities, external forces, and hydraulic disturbances; a fuzzy adaptive virtual model-based force planner that dynamically adjusts the desired leg forces in real time to minimize support force variations; and a DSTKF-based force controller that precisely regulates the output force of each leg. Simulations and physical experiments demonstrate that the proposed approach effectively achieves autonomous balance of ground contact forces and optimizes force distribution among the legs. This study provides a lightweight, fully closed-loop solution for state estimation and walking force balance in walking excavators equipped with standard proportional valves.

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Publication Details

Journal
Applied Sciences
Published
2025-11-29
DOI
https://doi.org/10.3390/app152312678
Primary Topic
Prosthetics and Rehabilitation Robotics
Type
article
Field-Weighted Citation Impact
0.00
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article

Balanced Walking Force Control for Walking Excavators Based on Dual Strong Tracking Kalman Filter

Daqing Zhang, Yi Zhang, Wenjie Yuan, Dongliang Chen et al.
Applied Sciences
Prosthetics and Rehabilitation Robotics
article

Balanced Walking Force Control for Walking Excavators Based on Dual Strong Tracking Kalman Filter

Daqing Zhang, Yi Zhang, Wenjie Yuan, Dongliang Chen, Zhen Liu
article en

Abstract

The operation of walking excavators on rugged terrain often leads to leg lift-off, which can result in uneven force distribution, accelerated structural wear, and even systemic instability. To address these issues, this paper proposes a coordinated control framework comprising three integral components: a Dual Strong Tracking Kalman Filter (DSTKF) for estimating unmeasurable system states—such as joint velocities, external forces, and hydraulic disturbances; a fuzzy adaptive virtual model-based force planner that dynamically adjusts the desired leg forces in real time to minimize support force variations; and a DSTKF-based force controller that precisely regulates the output force of each leg. Simulations and physical experiments demonstrate that the proposed approach effectively achieves autonomous balance of ground contact forces and optimizes force distribution among the legs. This study provides a lightweight, fully closed-loop solution for state estimation and walking force balance in walking excavators equipped with standard proportional valves.

Applied SciencesVol. 15(23)
Central South University (CN), Xiangtan University (CN)
Openalex Percentile: Top 63%
Prosthetics and Rehabilitation Robotics
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