{"title":"Adaptive Fuzzy Output Feedback Control for Input-saturated System Based on Nonlinear Tracking Differentiator","authors":"Guofa Sun, Hanbo Yu, Wei Wei","doi":"10.1109/DDCLS.2019.8909022","DOIUrl":null,"url":null,"abstract":"This paper proposes an adaptive fuzzy output feedback control approach based on nonlinear tracking differentiator for a class of strict feedback systems with input saturation, unknown nonlinear functions and unmeasurable states. Fuzzy logic systems(FLSs) are used to approximate the unknown nonlinear function and a fuzzy state observer is designed to estimate the unmeasured state of the system. The nonlinear tracking differentiator (TD)is used to estimate the differential of command signal which avoids the problem of “explosion of complexity” in traditional backstepping control. The compensation signal is introduced to eliminate the filtering error caused by the nonlinear tracking differentiator. The proposed approach guarantees stability of the closed-loop system and all signals are bounded. Finally, simulation examples are provided to check the effectiveness of the proposed approach.","PeriodicalId":6699,"journal":{"name":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"28 2 1","pages":"1306-1311"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS.2019.8909022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes an adaptive fuzzy output feedback control approach based on nonlinear tracking differentiator for a class of strict feedback systems with input saturation, unknown nonlinear functions and unmeasurable states. Fuzzy logic systems(FLSs) are used to approximate the unknown nonlinear function and a fuzzy state observer is designed to estimate the unmeasured state of the system. The nonlinear tracking differentiator (TD)is used to estimate the differential of command signal which avoids the problem of “explosion of complexity” in traditional backstepping control. The compensation signal is introduced to eliminate the filtering error caused by the nonlinear tracking differentiator. The proposed approach guarantees stability of the closed-loop system and all signals are bounded. Finally, simulation examples are provided to check the effectiveness of the proposed approach.