{"title":"柔性吸气式高超声速飞行器自适应区间2型模糊滑模控制器设计","authors":"Junlong Gao, Ruyi Yuan, J. Yi, Chengdong Li","doi":"10.1109/FUZZ-IEEE.2015.7337828","DOIUrl":null,"url":null,"abstract":"In this paper an adaptive interval type-2 fuzzy sliding mode controller, which is applied to flexible air-breathing hypersonic vehicle (FAHV) longitudinal model, is designed based on interval type-2 fuzzy logic systems (IT2-FLS) and sliding mode control (SMC) theory. In order to get FAHV longitudinal model stably controlled, we decouple the model into velocity and altitude channels through output feedback linearization. Moreover, due to the severe uncertainties which mainly come from unpredictable varying aerodynamic interferences and mutual couplings in airframe flexible modes and those difficulties of computing nonlinear functions with high-order derivatives under practical conditions, we design a sliding mode controller to achieve system convergence and adopt IT2-FLS to estimate the nonlinear functions with bounded parameter uncertainties online for counteracting the tracking errors and suppressing flexible vibrations. The adaptive law of interval type-2 fuzzy sliding mode controller is derived through Lyapunov synthesis approach. Furthermore, we adopt tracking differentiator (TD) and nonlinear state observer (NSO) algorithms to generate the real-time derivatives and high-order approximate commands in velocity and altitude channels, respectively. Several comparisons have been done in this paper and the simulation results validate the robustness and effectiveness of the proposed controller.","PeriodicalId":185191,"journal":{"name":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Adaptive interval type-2 fuzzy sliding mode controller design for flexible air-breathing hypersonic vehicles\",\"authors\":\"Junlong Gao, Ruyi Yuan, J. Yi, Chengdong Li\",\"doi\":\"10.1109/FUZZ-IEEE.2015.7337828\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper an adaptive interval type-2 fuzzy sliding mode controller, which is applied to flexible air-breathing hypersonic vehicle (FAHV) longitudinal model, is designed based on interval type-2 fuzzy logic systems (IT2-FLS) and sliding mode control (SMC) theory. In order to get FAHV longitudinal model stably controlled, we decouple the model into velocity and altitude channels through output feedback linearization. Moreover, due to the severe uncertainties which mainly come from unpredictable varying aerodynamic interferences and mutual couplings in airframe flexible modes and those difficulties of computing nonlinear functions with high-order derivatives under practical conditions, we design a sliding mode controller to achieve system convergence and adopt IT2-FLS to estimate the nonlinear functions with bounded parameter uncertainties online for counteracting the tracking errors and suppressing flexible vibrations. The adaptive law of interval type-2 fuzzy sliding mode controller is derived through Lyapunov synthesis approach. Furthermore, we adopt tracking differentiator (TD) and nonlinear state observer (NSO) algorithms to generate the real-time derivatives and high-order approximate commands in velocity and altitude channels, respectively. Several comparisons have been done in this paper and the simulation results validate the robustness and effectiveness of the proposed controller.\",\"PeriodicalId\":185191,\"journal\":{\"name\":\"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZ-IEEE.2015.7337828\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZ-IEEE.2015.7337828","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper an adaptive interval type-2 fuzzy sliding mode controller, which is applied to flexible air-breathing hypersonic vehicle (FAHV) longitudinal model, is designed based on interval type-2 fuzzy logic systems (IT2-FLS) and sliding mode control (SMC) theory. In order to get FAHV longitudinal model stably controlled, we decouple the model into velocity and altitude channels through output feedback linearization. Moreover, due to the severe uncertainties which mainly come from unpredictable varying aerodynamic interferences and mutual couplings in airframe flexible modes and those difficulties of computing nonlinear functions with high-order derivatives under practical conditions, we design a sliding mode controller to achieve system convergence and adopt IT2-FLS to estimate the nonlinear functions with bounded parameter uncertainties online for counteracting the tracking errors and suppressing flexible vibrations. The adaptive law of interval type-2 fuzzy sliding mode controller is derived through Lyapunov synthesis approach. Furthermore, we adopt tracking differentiator (TD) and nonlinear state observer (NSO) algorithms to generate the real-time derivatives and high-order approximate commands in velocity and altitude channels, respectively. Several comparisons have been done in this paper and the simulation results validate the robustness and effectiveness of the proposed controller.