This article explores the O(t^(-β))synchronization and asymptotic synchronization for fractional order BAM neural networks(FBAMNNs)with discrete delays,distributed delays and non-identical perturbations.By designing ...This article explores the O(t^(-β))synchronization and asymptotic synchronization for fractional order BAM neural networks(FBAMNNs)with discrete delays,distributed delays and non-identical perturbations.By designing a state feedback control law and a new kind of fractional order Lyapunov functional,a new set of algebraic sufficient conditions are derived to guarantee the O(t^(-β))Synchronization and asymptotic synchronization of the considered FBAMNNs model;this can easily be evaluated without using a MATLAB LMI control toolbox.Finally,two numerical examples,along with the simulation results,illustrate the correctness and viability of the exhibited synchronization results.展开更多
This article provides a graphical parameter tuning method of PI^λ controllers for fractional-order time-delay systems. First, the complete stabilizing region of PI^λ controller in proportional-integral plane, for a ...This article provides a graphical parameter tuning method of PI^λ controllers for fractional-order time-delay systems. First, the complete stabilizing region of PI^λ controller in proportional-integral plane, for a fixed A, is determined in terms of a graphical stability criterion applicable to fractional-delay systems. Then, the stabilizing region is maximized analytically with respect to parameter ）, to expect the most various behaviors of the closed-loop systems. Finally, by defining appropriate functions relative to the requirements of gain and phase margins, the curves in the maximized stabilizing region satisfying the pre-specified gain and phase margins are drawn, which releases a flexible parameter tuning procedure. Numerical examples are given to illustrate the design steps.展开更多
基金joint financial support of Thailand Research Fund RSA 6280004,RUSA-Phase 2.0 Grant No.F 24-51/2014-UPolicy(TN Multi-Gen),Dept.of Edn.Govt.of India,UGC-SAP(DRS-I)Grant No.F.510/8/DRS-I/2016(SAP-I)+1 种基金DST(FIST-level I)657876570 Grant No.SR/FIST/MS-I/2018/17Prince Sultan University for funding this work through research group Nonlinear Analysis Methods in Applied Mathematics(NAMAM)group number RG-DES-2017-01-17。
文摘This article explores the O(t^(-β))synchronization and asymptotic synchronization for fractional order BAM neural networks(FBAMNNs)with discrete delays,distributed delays and non-identical perturbations.By designing a state feedback control law and a new kind of fractional order Lyapunov functional,a new set of algebraic sufficient conditions are derived to guarantee the O(t^(-β))Synchronization and asymptotic synchronization of the considered FBAMNNs model;this can easily be evaluated without using a MATLAB LMI control toolbox.Finally,two numerical examples,along with the simulation results,illustrate the correctness and viability of the exhibited synchronization results.
基金supported by the National Natural Science Foundation of China (No. 60874028)
文摘This article provides a graphical parameter tuning method of PI^λ controllers for fractional-order time-delay systems. First, the complete stabilizing region of PI^λ controller in proportional-integral plane, for a fixed A, is determined in terms of a graphical stability criterion applicable to fractional-delay systems. Then, the stabilizing region is maximized analytically with respect to parameter ）, to expect the most various behaviors of the closed-loop systems. Finally, by defining appropriate functions relative to the requirements of gain and phase margins, the curves in the maximized stabilizing region satisfying the pre-specified gain and phase margins are drawn, which releases a flexible parameter tuning procedure. Numerical examples are given to illustrate the design steps.
