Fuzzy generalised predictive control for a class of fractional-order non-linear systems

被引：14

作者：

Wang, Bin ^{[1
]}

Shi, Ke ^{[2
]}

Yang, Lan ^{[3
]}

Wu, Fengjiao ^{[1
]}

Chen, Diyi ^{[1
]}

机构：

[1] Northwest A&F Univ, Dept Elect Engn, Yangling 712100, Shaanxi, Peoples R China

[2] South China Univ Technol, Sch Elect Power, Guangzhou 510641, Guangdong, Peoples R China

[3] Xi An Jiao Tong Univ, Sch Elect Engn, Xian 710049, Shaanxi, Peoples R China

来源：

IET CONTROL THEORY AND APPLICATIONS | 2018年 / 12卷 / 01期

关键词：

predictive control; fuzzy control; nonlinear control systems; linearisation techniques; autoregressive moving average processes; Laplace transforms; fuzzy generalised predictive control; fractional-order nonlinear systems; FFGPC; Grunwald-Letnikov fractional calculus; Laplace transform; controlled autoregressive integrating moving average model; Takagi-Sugeno fuzzy linearisation theory; linear CARMA model; CARMA predictive model; SLIDING MODE CONTROL; DYNAMIC-ANALYSIS; PERFORMANCE ANALYSIS; CHANCE CONSTRAINTS; STABILIZATION; SCHEME;

D O I：

10.1049/iet-cta.2017.0239

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Fractional-order fuzzy generalised predictive control (FFGPC) for a class of non-linear systems is studied. Based on the Grunwald-Letnikov fractional calculus, Laplace transform, and discretisation, a class of fractional-order non-linear systems are transformed to fit the standard controlled autoregressive integrating moving average (CARMA) model. With the help of the Takagi-Sugeno fuzzy linearisation theory, a linear CARMA model for the non-linear systems is represented. Then, a new FFGPC method is proposed for the fractional-order non-linear systems based on the obtained CARMA predictive model and generalised predictive control theory. Numerical simulations are implemented to verify the effectiveness and superiority of the new method. This work also provides a reference for the control of relevant fractional-order systems.

引用

页码：87 / 96

页数：10

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