scholarly journals Synchronization of Chaotic Fractional-Order Lu-Lu Systems with Active Sliding Mode Control

2014 ◽  
Vol 7 (9) ◽  
pp. 131-138 ◽  
Author(s):  
Mohamad Reza Dastranj ◽  
Aminreza Riahi ◽  
Mahboubeh Moghaddas
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Sliding Mode ◽  
Mode Control ◽  
Active Sliding Mode Control

scholarly journals SYNCHRONIZATION BETWEEN INTEGER AND FRACTIONAL ORDER DELAY NEURAL NETWORKS SYSTEM

2020 ◽  
Vol 2 (2) ◽  
pp. 121-126
Author(s):  
Fatin Nabila Abd Latiff ◽  
Wan Ainun Mior Othman
Keyword(s):  
Neural Networks ◽  
Sliding Mode Control ◽  
Fractional Order ◽  
Recurrent Neural Networks ◽  
Secure Communication ◽  
Sliding Mode ◽  
Mode Control ◽  
Synchronization Problem ◽  
Active Sliding Mode Control ◽  
Fractional Method

The purpose is to present a method for synchronizing a recurrent neural networks system between integer and fractional-order order delay by active sliding mode control . The Active Sliding Mode Control (ASMC) scheme is used to solve the synchronization problem between the integer-order delayed recurrent neural networks system via active sliding mode control (IoDRNNASM) systems and the fractional-order delay recurrent neural networks system via active sliding mode control (FoDRNNASM) system based on the Lyapunov direct fractional method (LDFM). To explore the behavior of the IoDRNNASM systems and the FoDRNNASM systems, we performed the technique of numerical simulations using MATLAB software to prove the feasibility and strength of the archived outcomes. This concept can also be enhanced with the implementation of double encryption using RSA encryption to secure communication. Because we expected in the future that this enhanced concept will strengthen and increase the network security capabilities that will provide powerful protection in secure communications.

A diffusive representation approach toward H∞ sliding mode control design for fractional-order Markovian jump systems

2020 ◽  
pp. 095965182097525
Author(s):  
Majid Parvizian ◽  
Khosro Khandani
Keyword(s):  
Sliding Mode Control ◽  
Fractional Order ◽  
Sliding Mode ◽  
Markovian Jump Systems ◽  
Markovian Jump ◽  
Suggested Approach ◽  
Stabilizing Controller ◽  
Mode Control ◽  
Jump Systems ◽  
Diffusive Representation

This article proposes a new [Formula: see text] sliding mode control strategy for stabilizing controller design for fractional-order Markovian jump systems. The suggested approach is based on the diffusive representation of fractional-order Markovian jump systems which transforms the fractional-order system into an integer-order one. Using a new Lyapunov–Krasovskii functional, the problem of [Formula: see text] sliding mode control of uncertain fractional-order Markovian jump systems with exogenous noise is investigated. We propose a sliding surface and prove its reachability. Moreover, the linear matrix inequality conditions for stochastic stability of the resultant sliding motion with a given [Formula: see text] disturbance attenuation level are derived. Eventually, the theoretical results are verified through a simulation example.

scholarly journals Observer-based adaptive neural network backstepping sliding mode control for switched fractional order uncertain nonlinear systems with unmeasured states

2021 ◽  
pp. 002029402110211
Author(s):  
Tao Chen ◽  
Damin Cao ◽  
Jiaxin Yuan ◽  
Hui Yang
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Sliding Mode Control ◽  
Fractional Order ◽  
Sliding Mode ◽  
Tracking Error ◽  
Adaptive Neural Network ◽  
Dynamic Surface ◽  
Mode Control ◽  
The Stability

This paper proposes an observer-based adaptive neural network backstepping sliding mode controller to ensure the stability of switched fractional order strict-feedback nonlinear systems in the presence of arbitrary switchings and unmeasured states. To avoid “explosion of complexity” and obtain fractional derivatives for virtual control functions continuously, the fractional order dynamic surface control (DSC) technology is introduced into the controller. An observer is used for states estimation of the fractional order systems. The sliding mode control technology is introduced to enhance robustness. The unknown nonlinear functions and uncertain disturbances are approximated by the radial basis function neural networks (RBFNNs). The stability of system is ensured by the constructed Lyapunov functions. The fractional adaptive laws are proposed to update uncertain parameters. The proposed controller can ensure convergence of the tracking error and all the states remain bounded in the closed-loop systems. Lastly, the feasibility of the proposed control method is proved by giving two examples.

Sign in / Sign up

Export Citation Format

Share Document