{"title":"非线性和不确定性CDC半主动悬架系统的线性变参数μ综合鲁棒控制","authors":"Farong Kou, Shenglin Li, Xudong Yang","doi":"10.1002/asjc.3520","DOIUrl":null,"url":null,"abstract":"<p>Because the continuous damping control (CDC) semi-active suspension system has complex nonlinear and uncertain characteristics that can significantly affect the performance of the system. And in the controller design process, achieving a balance of multiple performance objectives is often difficult. Therefore, this paper designs a linear parameter varying (LPV) <i>μ</i> synthesis robust controller for the vibration suppression and multi-objective control of a 7-degree-of-freedom (7-DOF) vehicle suspension system equipped with CDC dampers. Firstly, the nonlinear force model of the solenoid valve CDC damper is developed based on the actual damping variation. Considering the nonlinear forces of the coil springs, the nonlinear model of the 7-DOF suspension system is expressed as LPV form. Further, the linear fractional transformation (LFT) method is used to analyze and reconstruct the system model for multiple parameter uncertainties of the suspension. The actuator time delays are also simulated through a frequency domain transfer function, which is considered to be an unmodeled dynamic at the input of the system. Finally, an LPV-<i>μ</i> synthesis robust controller based on nonlinearity and mixed uncertainty is designed to improve car ride comfort and achieve the best relationship between comfort and handling stability. Simulation and experimental results under random disturbance conditions show that the LPV-<i>μ</i> synthesis controller has better anti-jamming performance and controllability compared to the <i>H</i><sub>∞</sub> controller and <i>μ</i> synthesis controller.</p>","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"27 3","pages":"1455-1478"},"PeriodicalIF":2.7000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Linear parameter varying μ synthesis robust control of CDC semi-active suspension system for nonlinearity and uncertainty\",\"authors\":\"Farong Kou, Shenglin Li, Xudong Yang\",\"doi\":\"10.1002/asjc.3520\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Because the continuous damping control (CDC) semi-active suspension system has complex nonlinear and uncertain characteristics that can significantly affect the performance of the system. And in the controller design process, achieving a balance of multiple performance objectives is often difficult. Therefore, this paper designs a linear parameter varying (LPV) <i>μ</i> synthesis robust controller for the vibration suppression and multi-objective control of a 7-degree-of-freedom (7-DOF) vehicle suspension system equipped with CDC dampers. Firstly, the nonlinear force model of the solenoid valve CDC damper is developed based on the actual damping variation. Considering the nonlinear forces of the coil springs, the nonlinear model of the 7-DOF suspension system is expressed as LPV form. Further, the linear fractional transformation (LFT) method is used to analyze and reconstruct the system model for multiple parameter uncertainties of the suspension. The actuator time delays are also simulated through a frequency domain transfer function, which is considered to be an unmodeled dynamic at the input of the system. Finally, an LPV-<i>μ</i> synthesis robust controller based on nonlinearity and mixed uncertainty is designed to improve car ride comfort and achieve the best relationship between comfort and handling stability. Simulation and experimental results under random disturbance conditions show that the LPV-<i>μ</i> synthesis controller has better anti-jamming performance and controllability compared to the <i>H</i><sub>∞</sub> controller and <i>μ</i> synthesis controller.</p>\",\"PeriodicalId\":55453,\"journal\":{\"name\":\"Asian Journal of Control\",\"volume\":\"27 3\",\"pages\":\"1455-1478\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Control\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/asjc.3520\",\"RegionNum\":4,\"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":"Asian Journal of Control","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/asjc.3520","RegionNum":4,"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}
Linear parameter varying μ synthesis robust control of CDC semi-active suspension system for nonlinearity and uncertainty
Because the continuous damping control (CDC) semi-active suspension system has complex nonlinear and uncertain characteristics that can significantly affect the performance of the system. And in the controller design process, achieving a balance of multiple performance objectives is often difficult. Therefore, this paper designs a linear parameter varying (LPV) μ synthesis robust controller for the vibration suppression and multi-objective control of a 7-degree-of-freedom (7-DOF) vehicle suspension system equipped with CDC dampers. Firstly, the nonlinear force model of the solenoid valve CDC damper is developed based on the actual damping variation. Considering the nonlinear forces of the coil springs, the nonlinear model of the 7-DOF suspension system is expressed as LPV form. Further, the linear fractional transformation (LFT) method is used to analyze and reconstruct the system model for multiple parameter uncertainties of the suspension. The actuator time delays are also simulated through a frequency domain transfer function, which is considered to be an unmodeled dynamic at the input of the system. Finally, an LPV-μ synthesis robust controller based on nonlinearity and mixed uncertainty is designed to improve car ride comfort and achieve the best relationship between comfort and handling stability. Simulation and experimental results under random disturbance conditions show that the LPV-μ synthesis controller has better anti-jamming performance and controllability compared to the H∞ controller and μ synthesis controller.
期刊介绍:
The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application.
Published six times a year, the Journal aims to be a key platform for control communities throughout the world.
The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive.
Topics include:
The theory and design of control systems and components, encompassing:
Robust and distributed control using geometric, optimal, stochastic and nonlinear methods
Game theory and state estimation
Adaptive control, including neural networks, learning, parameter estimation
and system fault detection
Artificial intelligence, fuzzy and expert systems
Hierarchical and man-machine systems
All parts of systems engineering which consider the reliability of components and systems
Emerging application areas, such as:
Robotics
Mechatronics
Computers for computer-aided design, manufacturing, and control of
various industrial processes
Space vehicles and aircraft, ships, and traffic
Biomedical systems
National economies
Power systems
Agriculture
Natural resources.