{"title":"A composite fixed-time sliding mode control scheme for Unmanned Ground Vehicles affected by external disturbances.","authors":"Zongliang Chen, Shuguo Pan, Kegen Yu, Xinhua Tang, Wang Gao, Haonan Jia","doi":"10.1016/j.isatra.2024.11.003","DOIUrl":null,"url":null,"abstract":"<p><p>Accurate path-following control is crucial for Unmanned Ground Vehicles (UGV). However, influenced by external disturbances, UGV systems encounter challenges in meeting specific performance requirements, such as no overshoot and minimized chattering. In current sliding mode control (SMC) methods with disturbance observer (DOB), there still exists a serious chattering problem. To achieve fast chattering reduction and accurate path-following performance, this paper proposes a novel composite fixed-time sliding mode (CFTSM) control method according to fixed-time disturbance observer (FTDO). First, a innovative CFTSM control scheme is developed to achieve a significant gain near the origin in the UGV system. It facilitates quicker convergence and improved tracking performance than other SMC methods. Then, to mitigate the impact of the external disturbances, a FTDO is designed to estimate and effectively eliminate these disturbances in fixed-time. Finally, a composite control strategy, which integrated the FTDO into the CFTSM control scheme, is proposed to stabilize the UGV system and suppress the chattering phenomenon. A comprehensive simulation and experimental results demonstrate that the proposed CFTSM-FTDO control strategy performs better with strong robustness and stability. In real experiments, the CFTSM achieves RMSE reductions of 26.8% and 8.9% in lateral and heading errors compared to CFTSM-FFE, and 19.1% and 3.9% compared to FTSMC-AESO. These enhancements are expected to achieve more accurate and stable tracking performance for the UGV, thus giving rise to accurate autonomous navigation.</p>","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISA transactions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.isatra.2024.11.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Accurate path-following control is crucial for Unmanned Ground Vehicles (UGV). However, influenced by external disturbances, UGV systems encounter challenges in meeting specific performance requirements, such as no overshoot and minimized chattering. In current sliding mode control (SMC) methods with disturbance observer (DOB), there still exists a serious chattering problem. To achieve fast chattering reduction and accurate path-following performance, this paper proposes a novel composite fixed-time sliding mode (CFTSM) control method according to fixed-time disturbance observer (FTDO). First, a innovative CFTSM control scheme is developed to achieve a significant gain near the origin in the UGV system. It facilitates quicker convergence and improved tracking performance than other SMC methods. Then, to mitigate the impact of the external disturbances, a FTDO is designed to estimate and effectively eliminate these disturbances in fixed-time. Finally, a composite control strategy, which integrated the FTDO into the CFTSM control scheme, is proposed to stabilize the UGV system and suppress the chattering phenomenon. A comprehensive simulation and experimental results demonstrate that the proposed CFTSM-FTDO control strategy performs better with strong robustness and stability. In real experiments, the CFTSM achieves RMSE reductions of 26.8% and 8.9% in lateral and heading errors compared to CFTSM-FFE, and 19.1% and 3.9% compared to FTSMC-AESO. These enhancements are expected to achieve more accurate and stable tracking performance for the UGV, thus giving rise to accurate autonomous navigation.