{"title":"使用积分二次约束的自主式水下航行器控制设计与分析","authors":"Sourav Sinha , Mazen Farhood , Daniel J. Stilwell","doi":"10.1016/j.conengprac.2024.106142","DOIUrl":null,"url":null,"abstract":"<div><div>This paper addresses the design and analysis of path-following controllers for an autonomous underwater vehicle (AUV) using a robustness analysis framework based on integral quadratic constraints (IQCs). The AUV is modeled as a linear fractional transformation (LFT) on uncertainties and is affected by exogenous inputs such as measurement noise and ocean currents. The proposed approach leverages a learning-based method to approximate the nonlinear hydrodynamic model with a linear parameter-varying one. Additionally, modeling uncertainties are incorporated into the other subsystem models of the AUV to capture the discrepancies between the outputs of the postulated mathematical abstractions and the experimental data. The resulting uncertain LFT system adequately captures the AUV behavior within a desired envelope. Ocean current disturbances are treated as uncertainties within the LFT system and properly characterized to reduce conservatism. The robust performance level, obtained from IQC analysis, serves as a qualitative measure of a controller’s performance, and is utilized in guiding the controller design process. The proposed approach is employed to design <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> and <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> controllers for the AUV. A comprehensive IQC-based analysis is subsequently conducted to demonstrate the robustness of the designed controllers to modeling uncertainties and disturbances. To validate the analysis results, extensive nonlinear simulations and underwater experiments are performed. The outcomes showcase the efficacy and reliability of the proposed approach in achieving robust control for the AUV.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Control design and analysis for autonomous underwater vehicles using integral quadratic constraints\",\"authors\":\"Sourav Sinha , Mazen Farhood , Daniel J. Stilwell\",\"doi\":\"10.1016/j.conengprac.2024.106142\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper addresses the design and analysis of path-following controllers for an autonomous underwater vehicle (AUV) using a robustness analysis framework based on integral quadratic constraints (IQCs). The AUV is modeled as a linear fractional transformation (LFT) on uncertainties and is affected by exogenous inputs such as measurement noise and ocean currents. The proposed approach leverages a learning-based method to approximate the nonlinear hydrodynamic model with a linear parameter-varying one. Additionally, modeling uncertainties are incorporated into the other subsystem models of the AUV to capture the discrepancies between the outputs of the postulated mathematical abstractions and the experimental data. The resulting uncertain LFT system adequately captures the AUV behavior within a desired envelope. Ocean current disturbances are treated as uncertainties within the LFT system and properly characterized to reduce conservatism. The robust performance level, obtained from IQC analysis, serves as a qualitative measure of a controller’s performance, and is utilized in guiding the controller design process. The proposed approach is employed to design <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> and <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> controllers for the AUV. A comprehensive IQC-based analysis is subsequently conducted to demonstrate the robustness of the designed controllers to modeling uncertainties and disturbances. To validate the analysis results, extensive nonlinear simulations and underwater experiments are performed. The outcomes showcase the efficacy and reliability of the proposed approach in achieving robust control for the AUV.</div></div>\",\"PeriodicalId\":50615,\"journal\":{\"name\":\"Control Engineering Practice\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Control Engineering Practice\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0967066124003010\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Control Engineering Practice","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967066124003010","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Control design and analysis for autonomous underwater vehicles using integral quadratic constraints
This paper addresses the design and analysis of path-following controllers for an autonomous underwater vehicle (AUV) using a robustness analysis framework based on integral quadratic constraints (IQCs). The AUV is modeled as a linear fractional transformation (LFT) on uncertainties and is affected by exogenous inputs such as measurement noise and ocean currents. The proposed approach leverages a learning-based method to approximate the nonlinear hydrodynamic model with a linear parameter-varying one. Additionally, modeling uncertainties are incorporated into the other subsystem models of the AUV to capture the discrepancies between the outputs of the postulated mathematical abstractions and the experimental data. The resulting uncertain LFT system adequately captures the AUV behavior within a desired envelope. Ocean current disturbances are treated as uncertainties within the LFT system and properly characterized to reduce conservatism. The robust performance level, obtained from IQC analysis, serves as a qualitative measure of a controller’s performance, and is utilized in guiding the controller design process. The proposed approach is employed to design and controllers for the AUV. A comprehensive IQC-based analysis is subsequently conducted to demonstrate the robustness of the designed controllers to modeling uncertainties and disturbances. To validate the analysis results, extensive nonlinear simulations and underwater experiments are performed. The outcomes showcase the efficacy and reliability of the proposed approach in achieving robust control for the AUV.
期刊介绍:
Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper.
The scope of Control Engineering Practice matches the activities of IFAC.
Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.