Hybrid Control Scheme for Projective Lag Synchronization of Riemann–Liouville Sense Fractional Order Memristive BAM NeuralNetworks with Mixed Delays
Grienggrai Rajchakit,
Anbalagan Pratap,
Ramachandran Raja,
Jinde Cao,
Jehad Alzabut and
Chuangxia Huang
Additional contact information
Grienggrai Rajchakit: Department of Mathematics, Maejo University, Chiangmai 50290, Thailand
Anbalagan Pratap: Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College, Avadi 600 062, India
Ramachandran Raja: Ramanujan Centre for Higher Mathematics, Alagappa University, Karaikudi 630 004, India
Jinde Cao: School of Mathematics, Southeast University, Nanjing 211189, China
Jehad Alzabut: Department of Mathematics and General Sciences, Prince Sultan University, 11586 Riyadh, Saudi Arabia
Chuangxia Huang: Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering, Department of Applied Mathematics, Changsha University of Science and Technology, Changsha 410114, China
Mathematics, 2019, vol. 7, issue 8, 1-23
Abstract:
This sequel is concerned with the analysis of projective lag synchronization of Riemann–Liouville sense fractional order memristive BAM neural networks (FOMBNNs) with mixed time delays via hybrid controller. Firstly, a new type of hybrid control scheme, which is the combination of open loop control and adaptive state feedback control is designed to guarantee the global projective lag synchronization of the addressed FOMBNNs model. Secondly, by using a Lyapunov–Krasovskii functional and Barbalet’s lemma, a new brand of sufficient criterion is proposed to ensure the projective lag synchronization of the FOMBNNs model considered. Moreover, as special cases by using a hybrid control scheme, some sufficient conditions are derived to ensure the global projective synchronization, global complete synchronization and global anti-synchronization for the FOMBNNs model considered. Finally, numerical simulations are provided to check the accuracy and validity of our obtained synchronization results.
Keywords: memristive BAM neural networks; hybrid control; mixed delays; synchronization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (11)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:7:y:2019:i:8:p:759-:d:258903
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