Stability analysis for discrete-time stochastic memristive neural networks with both leakage and probabilistic delays

Liu, Hongjian; Wang, Zidong; Shen, Bo; Huang, Tingwen; Alsaadi, Fuad E.

doi:10.1016/j.neunet.2018.02.003

Cited by 73 publications

(10 citation statements)

References 42 publications

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“…The Simulation results based on a high-fidelity veDYNA model validate the effectiveness of the proposed controller. Note that the faults in the in-wheel motors and sensors [31][32][33], the vibration control [34,35] for driving comfort and the time-delay problem in control implementation [36][37][38] are not considered, which are left for our future study.…”

Section: Resultsmentioning

confidence: 99%

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Fault‐tolerant path‐following control for in‐wheel‐motor‐driven autonomous ground vehicles with differential steering

Wang

Zong

Guo

et al. 2019

Asian Journal of Control

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Over the past several decades, the automobile industry has denoted significant research efforts to developing in-wheel-motor-driven autonomous ground vehicles (IWM-AGVs) with active front-wheel steering. One of the most fundamental issues for IWM-AGVs is path following, which is important for automated driving to ensure that the vehicle can track a target-planned path during local navigation. However, the path-following task may fail if the system experiences a stuck fault in the active front-wheel steering. In this paper, a fault-tolerant control (FTC) strategy is presented for the path following of IWM-AGVs in the presence of a stuck fault in the active front-wheel steering. For this purpose, differential steering is used to generate differential torque between the left and right wheels in IWM-AGVs, and an adaptive triple-step control approach is applied to realize coordinated lateral and longitudinal path-following maneuvering. The parameter uncertainties for the cornering stiffness and external disturbances are considered to make the vehicles robust to different driving environments. The effectiveness of the proposed scheme is evaluated with a high-fidelity and full-car model based on the veDYNA-Simulink joint platform.

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Section: Resultsmentioning

confidence: 99%

“…Taking the time derivative of V (41) along the error dynamics (24), (34), and (35) and then canceling unknown parameters by means of (29), (37) and (39), we havė…”

Section: Robustly Asymptotically Tracking If the Dis-mentioning

confidence: 99%

Fault‐tolerant path‐following control for in‐wheel‐motor‐driven autonomous ground vehicles with differential steering

Wang

Zong

Guo

et al. 2019

Asian Journal of Control

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“…As we all know, the stability is one of the most important factors in the system analysis and it is also a prerequisite ensuring the normal system operations (Hu, Zhang, Kao, et al, 2019;Hu, Zhang, Yu, et al, 2019;Tong et al, 2020;Zou et al, 2019). Therefore, the increasing research attention has been focused on the stability analysis of the systems and the most widely studied method is based on the Lyapunov stability (Jiao et al, 2019;H. Liu et al, 2018;Y.…”

Section: Introductionmentioning

confidence: 99%

Finite-time memory fault detection filter design for nonlinear discrete systems with deception attacks

Chen

et al. 2020

International Journal of Systems Science

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In this paper, the finite-time memory fault detection filter (MFDF) is designed for nonlinear discrete systems with randomly occurring deception attacks, where the phenomenon of the randomly occurring deception attacks is characterised by a Bernoulli distributed random variable with known probability. To be specific, the finite-horizon data are employed to construct the MFDF. The main purpose of this paper is to design the MFDF such that, for all nonlinearities, external disturbances and randomly occurring deception attacks, the resultant augmented system is finite-time stable and attains the H ∞ performance. Accordingly, some sufficient conditions are developed to guarantee the existence of the desired fault detection filter parameters, where the solvability of the addressed problem is verified by the feasibility of certain matrix inequalities. Moreover, in order to show that the MFDF has better detection performance, a non-memory fault detection filter (NMFDF) is constructed to compare with the MFDF. Finally, two numerical simulations are utilised to illustrate the effectiveness of the proposed fault detection strategies and explain the superiority of the proposed MFDF.

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“…Most recently, based on event-triggered communication protocol, a state estimator has been proposed for complex dynamical networks with random sensor delays and coupling strengths (Hu et al, 2020). Similarly, nonlinear perturbations, parameter uncertainties and controller gain variations may also take place randomly, and these randomly occurring phenomena will make the analysis and synthesis problems more complex and difficult (Ali et al, 2018;Ding et al, 2015;Dong et al, 2011;Liang et al, 2014;Liu et al, 2018;Ma et al, 2011;Rakkiyappan et al, 2016). Some recent results on Markov jump systems with randomly occurring delays and nonlinearities have been reported in Wu et al (2014) and Xu et al (2018) and the references therein.…”

Section: Introductionmentioning

confidence: 99%

Observer-based passive control of non-homogeneous Markov jump systems with random communication delays

Chen

et al. 2020

International Journal of Systems Science

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This paper focuses on the passive control problem for Markov jump systems with piecewise-constant transition rates, random nonlinearities and random communication delays. An observer is used to obtain the system state, and communication delay with probabilistic distribution is considered. The probabilistic properties of the nonlinear perturbations and communication delays are described by two mutually independent Bernoulli sequences. Based on average dwell time method and Lyapunov stability theory, a sufficient stochastic passivity condition is presented. By singular value decomposition technique the gain matrices can be computed via strict linear matrix inequalities, and the desired controller guarantees the stochastic passivity of the closed-loop augmented system. The effectiveness of the method is illustrated by a numerical example.

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Stability analysis for discrete-time stochastic memristive neural networks with both leakage and probabilistic delays

Cited by 73 publications

References 42 publications

Fault‐tolerant path‐following control for in‐wheel‐motor‐driven autonomous ground vehicles with differential steering

Fault‐tolerant path‐following control for in‐wheel‐motor‐driven autonomous ground vehicles with differential steering

Finite-time memory fault detection filter design for nonlinear discrete systems with deception attacks

Observer-based passive control of non-homogeneous Markov jump systems with random communication delays

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