Finite-Time Robust Synchronization of Delayed Competitive Neural Networks via Sliding-Mode Control

2021 ◽  
Author(s):  
Xingxing Tan ◽  
Leimin Wang ◽  
Xili Chen ◽  
Jiajun Cheng ◽  
Shan Jiang
Keyword(s):  
Neural Networks ◽  
Sliding Mode Control ◽  
Finite Time ◽  
Sliding Mode ◽  
Mode Control ◽  
Robust Synchronization

scholarly journals Finite-time Projective Synchronization for Semi-markovian Neural Networks Systems via Event-triggered Sliding Mode Control

2021 ◽  
Author(s):  
Junchao Ren ◽  
xuejiao Li
Keyword(s):  
Neural Networks ◽  
Sliding Mode Control ◽  
Finite Time ◽  
Sliding Mode ◽  
Projective Synchronization ◽  
Linear Matrix ◽  
Markov Jump ◽  
Mode Control ◽  
Markov Jump System ◽  
Event Triggered

Abstract This paper investigates the projection synchronization problem of stochastic neural networked systems based on event-triggered sliding mode control (SMC) covering a finite-time period. For improve transmission efficiency and save network resources, a related event-triggered scheme is proposed for the error system, which can identify whether the measurement error should be transmitted to the controller. For finite-time projective synchronization under given event-triggered mechanism, a semi-Markov jump system model is proposed. Secondly, by creating Lyapunov Krasovsky functional and using linear matrix inequality (LMI) technology, as well as considering a proper sliding surface, a sliding mode controller is designed to implement finite-time projection synchronization of different neural networks. Finally, numerical simulations are exploited to illustrate the effectiveness of the main results.

Continuous Finite-Time Integral Sliding Mode Control for Attitude Stabilization

2020 ◽  
Vol 67 (10) ◽  
pp. 2084-2088
Author(s):  
Lei Wang ◽  
Zhuoyue Song ◽  
Xiangdong Liu ◽  
Zhen Li ◽  
Tyrone Fernando ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Finite Time ◽  
Sliding Mode ◽  
Integral Sliding Mode Control ◽  
Integral Sliding Mode ◽  
Attitude Stabilization ◽  
Mode Control ◽  
Time Integral

scholarly journals Finite-Time Adaptive Higher-Order SMC for the Nonlinear Five DOF Active Magnetic Bearing System

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1333
Author(s):  
Sudipta Saha ◽  
Syed Muhammad Amrr ◽  
Abdelaziz Salah Saidi ◽  
Arunava Banerjee ◽  
M. Nabi
Keyword(s):  
Sliding Mode Control ◽  
Finite Time ◽  
Sliding Mode ◽  
A Priori ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Mode Control ◽  
Adaptive Laws ◽  
Effective Performance ◽  
Unknown Disturbances

The active magnetic bearings (AMB) play an essential role in supporting the shaft of fast rotating machines and controlling the displacements in the rotors due to the deviation in the shaft. In this paper, an adaptive integral third-order sliding mode control (AITOSMC) is proposed. The controller suppresses the deviations in the rotor and rejects the system uncertainties and unknown disturbances present in the five DOF AMB system. The application of AITOSMC alleviates the problem of high-frequency switching called chattering, which would otherwise restrict the practical application of sliding mode control (SMC). Moreover, adaptive laws are also incorporated in the proposed approach for estimating the controller gains. Further, it also prevents the problem of overestimation and avoids the use of a priori assumption about the upper bound knowledge of total disturbance. The Lyapunov and homogeneity theories are exploited for the stability proof, which guarantees the finite-time convergence of closed-loop and output signals. The numerical analysis of the proposed strategy illustrates the effective performance. Furthermore, the comparative analysis with the existing control schemes demonstrates the efficacy of the proposed controller.

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