M.J. Mahmoodabadi , N. Nejadkourki , M. Yousef Ibrahim
{"title":"五自由度主动悬架系统的最优模糊鲁棒状态反馈控制","authors":"M.J. Mahmoodabadi , N. Nejadkourki , M. Yousef Ibrahim","doi":"10.1016/j.rico.2024.100504","DOIUrl":null,"url":null,"abstract":"<div><div>Active suspension systems are integral to modern vehicles, enhancing driving comfort by addressing road irregularities and isolating the vehicle's interior from vibrations. In this research, we construct an active suspension system with five degrees of freedom (DOF) and find the best fuzzy robust state feedback controller to control it. While designing the state feedback controller, we considered the initial errors in the relative displacement and acceleration as well as their derivatives. A singleton fuzzifier, center average russification, and product inference engine are all control parameters managed by a fuzzy system. Optimization using the Sine Cosine Algorithm (SCA) is then used to determine the optimal gains for the controller that has been constructed. The technique uses two objective functions for depreciation: the body's acceleration, the relative displacement between the tire and sprung mass. Results show that the suggested active suspension system is better than that of previous studies.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"17 ","pages":"Article 100504"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal fuzzy robust state feedback control for a five DOF active suspension system\",\"authors\":\"M.J. Mahmoodabadi , N. Nejadkourki , M. Yousef Ibrahim\",\"doi\":\"10.1016/j.rico.2024.100504\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Active suspension systems are integral to modern vehicles, enhancing driving comfort by addressing road irregularities and isolating the vehicle's interior from vibrations. In this research, we construct an active suspension system with five degrees of freedom (DOF) and find the best fuzzy robust state feedback controller to control it. While designing the state feedback controller, we considered the initial errors in the relative displacement and acceleration as well as their derivatives. A singleton fuzzifier, center average russification, and product inference engine are all control parameters managed by a fuzzy system. Optimization using the Sine Cosine Algorithm (SCA) is then used to determine the optimal gains for the controller that has been constructed. The technique uses two objective functions for depreciation: the body's acceleration, the relative displacement between the tire and sprung mass. Results show that the suggested active suspension system is better than that of previous studies.</div></div>\",\"PeriodicalId\":34733,\"journal\":{\"name\":\"Results in Control and Optimization\",\"volume\":\"17 \",\"pages\":\"Article 100504\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Results in Control and Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666720724001334\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Results in Control and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666720724001334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
Optimal fuzzy robust state feedback control for a five DOF active suspension system
Active suspension systems are integral to modern vehicles, enhancing driving comfort by addressing road irregularities and isolating the vehicle's interior from vibrations. In this research, we construct an active suspension system with five degrees of freedom (DOF) and find the best fuzzy robust state feedback controller to control it. While designing the state feedback controller, we considered the initial errors in the relative displacement and acceleration as well as their derivatives. A singleton fuzzifier, center average russification, and product inference engine are all control parameters managed by a fuzzy system. Optimization using the Sine Cosine Algorithm (SCA) is then used to determine the optimal gains for the controller that has been constructed. The technique uses two objective functions for depreciation: the body's acceleration, the relative displacement between the tire and sprung mass. Results show that the suggested active suspension system is better than that of previous studies.