{"title":"欠驱动海洋车辆的非线性滑模预测轨迹跟踪控制:理论与实验","authors":"Run‐Zhi Wang, Li‐Ying Hao, Zhi‐Jie Wu","doi":"10.1002/rnc.7638","DOIUrl":null,"url":null,"abstract":"This article introduces a control method for trajectory tracking of underactuated unmanned marine vehicles (UMVs), employing the sliding mode predictive control (SMPC) scheme. To address the challenges of demonstrating system stability with a local feedback controller for underactuated UMVs in model predictive control (MPC), this article proposes an auxiliary controller design method based on sliding mode control. A sliding mode dynamic is derived through an error system and sliding surface equations. Compared to existing literature, which predominantly emphasizes demonstrating input‐state stability, this strategy ensures the asymptotic stability of the closed‐loop system by introducing a novel method for selecting weight matrices. Furthermore, extended terminal sets and feasible sets constructed via sliding variables are provided, thereby reducing conservatism. Ultimately, the SMPC scheme is validated through simulation and hardware experiments providing quantitative evidence of its effectiveness in real‐world applications.","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"45 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nonlinear sliding mode predictive trajectory tracking control of underactuated marine vehicles: Theory and experiment\",\"authors\":\"Run‐Zhi Wang, Li‐Ying Hao, Zhi‐Jie Wu\",\"doi\":\"10.1002/rnc.7638\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article introduces a control method for trajectory tracking of underactuated unmanned marine vehicles (UMVs), employing the sliding mode predictive control (SMPC) scheme. To address the challenges of demonstrating system stability with a local feedback controller for underactuated UMVs in model predictive control (MPC), this article proposes an auxiliary controller design method based on sliding mode control. A sliding mode dynamic is derived through an error system and sliding surface equations. Compared to existing literature, which predominantly emphasizes demonstrating input‐state stability, this strategy ensures the asymptotic stability of the closed‐loop system by introducing a novel method for selecting weight matrices. Furthermore, extended terminal sets and feasible sets constructed via sliding variables are provided, thereby reducing conservatism. Ultimately, the SMPC scheme is validated through simulation and hardware experiments providing quantitative evidence of its effectiveness in real‐world applications.\",\"PeriodicalId\":50291,\"journal\":{\"name\":\"International Journal of Robust and Nonlinear Control\",\"volume\":\"45 1\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Robust and Nonlinear Control\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1002/rnc.7638\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Robust and Nonlinear Control","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1002/rnc.7638","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Nonlinear sliding mode predictive trajectory tracking control of underactuated marine vehicles: Theory and experiment
This article introduces a control method for trajectory tracking of underactuated unmanned marine vehicles (UMVs), employing the sliding mode predictive control (SMPC) scheme. To address the challenges of demonstrating system stability with a local feedback controller for underactuated UMVs in model predictive control (MPC), this article proposes an auxiliary controller design method based on sliding mode control. A sliding mode dynamic is derived through an error system and sliding surface equations. Compared to existing literature, which predominantly emphasizes demonstrating input‐state stability, this strategy ensures the asymptotic stability of the closed‐loop system by introducing a novel method for selecting weight matrices. Furthermore, extended terminal sets and feasible sets constructed via sliding variables are provided, thereby reducing conservatism. Ultimately, the SMPC scheme is validated through simulation and hardware experiments providing quantitative evidence of its effectiveness in real‐world applications.
期刊介绍:
Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.