Predictive Sliding Mode Tracking Control for a Class of SISO Systems

被引：0
|
作者：
Truong Quang Dinh [1 ]
Iwasaki, Makoto [2 ]
Yoon, Jong Il [3 ]
Senatore, Adolfo [4 ]
Kang, Myeong Cheol [3 ]
机构：
[1] Univ Warwick, Warwick Mfg Grp, Coventry, W Midlands, England
[2] Nagoya Inst Technol, Dept Elec & Mech Engn, Nagoya, Aichi, Japan
[3] Korea Construct Equipment Technol Inst KOCETI, Gunsan 54004, South Korea
[4] Univ Salerno, Dept Ind Engn DIIN, I-84084 Fisciano, Italy
来源：
IECON 2018 - 44TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY | 2018年
关键词：
nonlinear system; sliding mode control; fuzzy; fuzzy cognitive map; grey predictor; GREY PREDICTOR;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper aims to develop a predictive sliding mode controller (PSMC) for a class of nonlinear SISO systems. The PSMC is designed as the combination of an adaptive sliding mode controller (ASMC) and an adaptive grey predictor (AGP). The ASMC is designed to ensure robust tracking performance of a nonlinear system which is represented by advanced fuzzy sets. Meanwhile, the AGP is used to estimate impacts of system uncertainties and disturbances on the performance in order to regulate the ASMC adaptive gain to minimize the control efforts while improving the control quality. Real-time experiments are carried out to validate the effectiveness and applicability of the proposed control scheme.
引用
收藏
页码：4545 / 4551
页数：7
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