Dissipative Sliding-Mode Synchronization Control of Uncertain Complex-Valued Inertial Neural Networks: Non-Reduced-Order Strategy

Citations

WEB OF SCIENCE

38
Citations

SCOPUS

40

초록

This study investigates the dissipative synchronization of uncertain complex-valued inertial neural networks with external disturbances using sliding mode control (SMC). In the absence of both variable substitution as well as the equivalent transformations of real-and complex-valued systems, this study focuses directly on the original complex-valued inertial system. First, a suitable integral switching surface (SS) function is proposed. Second, by constructing innovative Lyapunov-Krasovskii functionals and applying the Wirtinger-based integral inequality and reciprocally convex approach, a synchronization criterion is derived on the basis of the linear matrix inequality technique to ensure that the sliding mode dynamics are stable and dissipative. Then, an SMC law and an adaptive SMC law are designed, and the accessibility analysis of the predefined SS is provided. Numerical verifications as well as the superiority and practicality analysis of the proposed approach are provided through four examples.

키워드

Synchronizationcomplex-valued neural networkssliding mode controlinertial termtime-varying delaysEXPONENTIAL SYNCHRONIZATIONFINITE-TIMESYSTEMSSTABILITYDELAY
제목
Dissipative Sliding-Mode Synchronization Control of Uncertain Complex-Valued Inertial Neural Networks: Non-Reduced-Order Strategy
저자
Guo, RunanXu, ShengyuanAhn, Choon Ki
DOI
10.1109/TCSI.2022.3220428
발행일
2023-02-01
유형
Article
저널명
IEEE Transactions on Circuits and Systems I: Regular Papers
70
2
페이지
860 ~ 871