Synchronization of fractional-order delayed neural networks using dynamic-free adaptive sliding mode control
In this work, a dynamic-free adaptive sliding mode control (adaptive-SMC) methodology for
the synchronization of a specific class of chaotic delayed fractional-order neural network …
the synchronization of a specific class of chaotic delayed fractional-order neural network …
Stability and Synchronization of Delayed Quaternion-Valued Neural Networks under Multi-Disturbances
J Yang, X Xu, Q Xu, H Yang, M Yu - Mathematics, 2024 - mdpi.com
This paper discusses a type of mixed-delay quaternion-valued neural networks (QVNNs)
under impulsive and stochastic disturbances. The considered QVNNs model are treated as …
under impulsive and stochastic disturbances. The considered QVNNs model are treated as …
Resilient sampled-data control for fractional-order PMVG-based WTS with actuator saturation and probabilistic faults using fuzzy Lyapunov function method
G Narayanan, JJ Hoon, JY Hoon - Information Sciences, 2025 - Elsevier
The goal of this study is to present a new fuzzy Lyapunov function-based resilient sampled-
data control method for a fractional-order permanent magnet vernier generator (PMVG) …
data control method for a fractional-order permanent magnet vernier generator (PMVG) …
Adaptive Terminal Sliding-Mode Synchronization Control with Chattering Elimination for a Fractional-Order Chaotic System
C Wang - Fractal and Fractional, 2024 - mdpi.com
In this paper, an adaptive terminal sliding-mode control (ATSMC) method is proposed for the
synchronization of uncertain fractional-order chaotic systems with disturbances. According to …
synchronization of uncertain fractional-order chaotic systems with disturbances. According to …
A new fractional-order 3-D jerk chaotic system with no equilibrium point and its bifurcation analysis
Fractional-order chaotic systems have many applications in science and engineering. This
work describes a new fractional-order 3-D jerk chaotic system with no equilibrium point. The …
work describes a new fractional-order 3-D jerk chaotic system with no equilibrium point. The …
Finite-Time Adaptive Event-Triggered Control for Full States Constrained FONSs with Uncertain Parameters and Disturbances
C Wang, W Li, M Liang - Fractal and Fractional, 2024 - mdpi.com
This article focuses the event-triggered adaptive finite-time control scheme for the states
constrained fractional-order nonlinear systems (FONSs) under uncertain parameters and …
constrained fractional-order nonlinear systems (FONSs) under uncertain parameters and …
Further Stability Criteria for Sampled-Data-Based Dynamic Positioning Ships Using Takagi–Sugeno Fuzzy Models
M Zheng, Y Su, C Yan - Symmetry, 2024 - mdpi.com
This article discusses the stability problem of sampled-data-based dynamic positioning
ships (DPSs) using Takagi–Sugeno (TS) fuzzy models. Firstly, dynamic equations for …
ships (DPSs) using Takagi–Sugeno (TS) fuzzy models. Firstly, dynamic equations for …
Robust sampled-data synchronization of chaotic fractional variable order neural networks with time delays
R Kiruthika, A Manivannan - The European Physical Journal Special …, 2024 - Springer
This paper investigates the synchronization problem of master and slave fractional variable-
order delayed neural networks (FVODNNs) under the sampled-data control (SDC) scheme …
order delayed neural networks (FVODNNs) under the sampled-data control (SDC) scheme …
Synchronization of fractional order time delayed neural networks using matrix measure approach
S Jose, V Parthiban - The European Physical Journal Special Topics, 2024 - Springer
This research delves into the utilization of the matrix measure approach (MMA) for the
synchronization of fractional order neural networks (FONNs) incorporating time delays. This …
synchronization of fractional order neural networks (FONNs) incorporating time delays. This …
Synchronization and control for directly coupled reaction–diffusion neural networks with multiweights and hybrid coupling
This paper mainly deals with the synchronization and pinning control for multiweighted,
directly, and hybridly coupled reaction–diffusion neural networks (MDHCRDNNs). Different …
directly, and hybridly coupled reaction–diffusion neural networks (MDHCRDNNs). Different …