Fuzzy‐model‐based sampled‐data chaotic synchronisation under the input constraints consideration. Issue 2 (1st January 2019)

• Record Type: Journal Article
• Authors: Kim, Han Sol; Park, Jin Bae; Joo, Young Hoon
• Is Part Of: IET control theory & applications. Volume 13:Issue 2(2019)
• Page Start: 288
• Page End: 296
• Publication Date: 2019-01-01
• Subjects: feedback -- linear matrix inequalities -- synchronisation -- nonlinear control systems -- chaos -- sampled data systems -- fuzzy control -- stability -- Lyapunov methods; fuzzy‐model‐based sampled‐data chaotic synchronisation -- sampled‐data chaos synchronisation controller -- drive chaotic system -- response chaotic system -- constant sampling period -- linear matrix inequality‐based sufficient conditions -- modelling error term -- synchronisation performance -- input constraints -- sampled‐data fuzzy chaotic synchronisation -- feedback -- state vectors -- synchronisation error dynamics stabilisaion -- H‐infinity criterion -- identical chaotic systems synchronisation -- time‐dependent fuzzy Lyapunov–Krasovskii functional; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2018.5117
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : In this study, the authors propose a novel sampled‐data fuzzy chaotic synchronisation scheme under the input constraints consideration. The sampled‐data chaos synchronisation controller feedbacks the synchronisation error between the state vectors of both the drive chaotic system and the response chaotic system at a constant sampling period. The chaotic synchronisation is achieved by stabilising the synchronisation error dynamics based on the H‐infinity criterion. Linear matrix inequality‐based sufficient conditions for synchronising two identical chaotic systems are derived based on the newly proposed time‐dependent fuzzy Lyapunov–Krasovskii functional. Unlike previous approaches, the modelling error term is fully addressed so as to enhance the synchronisation performance. Finally, the effectiveness of the proposed method is validated through a numerical example.