Sliding Mode Control of FMII Systems: Handling Rice Fading Issues Under 2-D Frame

被引:3
|
作者
Lv, Xinyu [1 ,2 ]
Niu, Yugang [1 ]
Park, Ju H. [2 ]
机构
[1] East China Univ Sci & Technol, Minist Educ, Key Lab Smart Mfg Energy Chem Proc, Shanghai 200237, Peoples R China
[2] Yeungnam Univ, Minist Educ, Dept Elect Engn, Gyongsan 38541, South Korea
基金
新加坡国家研究基金会;
关键词
Optimization algorithm; previous state signals; rice fading model; sliding mode control (SMC); two-dimensional (2-D) Fornasini-Marchesini (FMII) system; NETWORKED SYSTEMS; STABILIZATION; SUBJECT;
D O I
10.1109/TSMC.2023.3287179
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Lth order Rice model can effectively describe imperfect transmission, including amplitude attenuation, time delays, and stochastic disturbance, and is a popular channel fading model in one-dimensional (1-D) systems. However, due to the state evolution feature of two-dimensional (2-D) systems, the previous state signals of 2-D systems are not as directly determinable as those of 1-D systems such that the construction of the conventional and obvious Lth order Rice model become difficulty for 2-D systems. Motivated by these, this work will investigate the sliding mode control (SMC) problem of the 2-D Fornasini-Marchesini (FMII) system under Rice fading channels. First, the previous p-step state signals are defined according to the evolution feature of the FMII model. Afterwards, a new applicable Lth-order Rice fading model for 2-D FMII systems is constructed, which not only has 2-D structural characteristics but also has similar properties to 1-D cases. A 2-D-type sliding function involving the predefined previous L-step state signals and channel attenuation coefficients is designed, which exhibits a similar structural feature to the FMII model. A feasible SMC law is designed via the available fading states to achieve the ultimately uniformly boundedness in the mean square of the closed-loop system and the reachability of the sliding domain around the specified sliding surface. Furthermore, an optimization-solving algorithm is introduced to minimize the convergent bound. Finally, an example is applied to demonstrated the proposed results.
引用
收藏
页码:6909 / 6920
页数:12
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