Fractional order integral sliding mode controller based on neural network: theory and electro-hydraulic benchmark test

2021 ◽  
pp. 1-1
Author(s):  
Hai-Peng Ren ◽  
Shan-Shan Jiao ◽  
Xuan Wang ◽  
Okyay Kaynak
Keyword(s):  
Neural Network ◽  
Fractional Order ◽  
Network Theory ◽  
Sliding Mode ◽  
Sliding Mode Controller ◽  
Benchmark Test ◽  
Integral Sliding Mode ◽  
Neural Network Theory ◽  
Fractional Order Integral

Robust Fault Identification of Turbofan Engines Sensors Based on Fractional-Order Integral Sliding Mode Observer

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Xiaocong He ◽  
Lingfei Xiao
Keyword(s):  
Fractional Order ◽  
Sliding Mode ◽  
Sliding Mode Observer ◽  
Fault Identification ◽  
Integral Sliding Mode ◽  
Turbofan Engines ◽  
System A ◽  
Fault Reconstruction ◽  
Integral Sliding Surface ◽  
Fractional Order Integral

Abstract This paper presents a robust fault identification scheme based on fractional-order integral sliding mode observer (FOISMO) for turbofan engine sensors with uncertainties. The equilibrium manifold expansion (EME) model is introduced due to its simplicity and accuracy for nonlinear system. A fractional-order integral sliding mode observer is designed to reconstruct faults on sensors, in which the fractional-order integral sliding surface guarantees the fast convergence of reconstruction. The observer parameters is selected according to L2 gain theory in order to minimize the effect of uncertainties on the fault reconstruction signal. Simulations in Matlab/Simulink show high reconstruction accuracy of the proposed method despite the present of uncertainties.

scholarly journals Fractional-Order Sliding Mode Synchronization for Fractional-Order Chaotic Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Chenhui Wang
Keyword(s):  
Fractional Order ◽  
Chaotic Systems ◽  
Sliding Mode ◽  
Sufficient Conditions ◽  
Synchronization Error ◽  
Sliding Mode Controller ◽  
Sliding Surface ◽  
Numerical Examples ◽  
Mode Synchronization ◽  
Fractional Order Integral

Some sufficient conditions, which are valid for stability check of fractional-order nonlinear systems, are given in this paper. Based on these results, the synchronization of two fractional-order chaotic systems is investigated. A novel fractional-order sliding surface, which is composed of a synchronization error and its fractional-order integral, is introduced. The asymptotical stability of the synchronization error dynamical system can be guaranteed by the proposed fractional-order sliding mode controller. Finally, two numerical examples are given to show the feasibility of the proposed methods.

scholarly journals Projective Synchronization of Nonidentical Fractional-Order Memristive Neural Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Chong Chen ◽  
Zhixia Ding
Keyword(s):  
Neural Networks ◽  
Fractional Order ◽  
Sliding Mode ◽  
Direct Method ◽  
Projective Synchronization ◽  
Sliding Mode Controller ◽  
Memristive Neural Networks ◽  
Lyapunov Direct Method ◽  
Sliding Motion ◽  
Fractional Order Integral

This paper investigates projective synchronization of nonidentical fractional-order memristive neural networks (NFMNN) via sliding mode controller. Firstly, based on the sliding mode control theory, a new fractional-order integral sliding mode controller is designed to ensure the occurrence of sliding motion. Furthermore, according to fractional-order differential inequalities and fractional-order Lyapunov direct method, the trajectories of the system converge to the sliding mode surface to carry out sliding mode motion, and some sufficient criteria are obtained to achieve global projective synchronization of NFMNN. In addition, the conclusions extend and improve some previous works on the synchronization of fractional-order memristive neural networks (FMNN). Finally, a simulation example is given to verify the effectiveness and correctness of the obtained results.

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