Exponential stability of impulsive systems with random delays under sampled‐data control

Subramanian, K.; Muthukumar, P.; Zhu, Quanxin

doi:10.1049/iet-cta.2017.0503

Cited by 8 publications

(11 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(1) V( ) = 0 ⇐⇒ = 0, (2) for some , > 0, 0 < p < 1, q > 1, any solution y(t) of system (19) satisfies the inequality…”

Section: Lemma 22 ( 22mentioning

confidence: 99%

“…Cao et al 10 discussed the stabilization of MNNs by designing appropriate event-based controllers, while Wang et al 11 proved that the stabilization of MNNs by using the fuzzy membership functions-dependent on Lyapunov-Krasovskii functional. The existence and exponential stabilization of the system at the equilibrium point were discussed in other studies, [12][13][14][15][16] and the exponential synchronization and stabilization of NNs were investigated in other studies [17][18][19][20][21] by adopting the sampled-data control.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exponential and fixed‐time stabilization of memristive neural networks with mixed delays

Liu

Gao

2021

Math Methods in App Sciences

View full text Add to dashboard Cite

In this paper, we study a class of memristive neural networks with mixed delays. The existence of its equilibrium point is proved without the boundedness and initial value of the activation function, and a criterion to ensure its exponential stabilization under a sampled-data controller is obtained by constructing an appropriate Lyapunov function. Meanwhile, the fixed-time stabilization of memristive neural networks is also proved by the Lyapunov method. The obtained results extend and enhance some existing ones, and are illustrated by numerical examples.

show abstract

“…(1) V( ) = 0 ⇐⇒ = 0, (2) for some , > 0, 0 < p < 1, q > 1, any solution y(t) of system (19) satisfies the inequality…”

Section: Lemma 22 ( 22mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exponential and fixed‐time stabilization of memristive neural networks with mixed delays

Liu

Gao

2021

Math Methods in App Sciences

View full text Add to dashboard Cite

show abstract

“…On the basis of [12], Li and Wu [13] use the state observer as the state feedback to establish the closed-loop augmented system and design the controller with exponential stability of mean square. In reference [14], the stability analysis of nonlinear disturbance and random time delay in the sampling process was studied. Obviously, none of the above random delay stability design problems take system failure into consideration.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Robust H2/H∞ Fault-Tolerant Control with Random Delay NCS

Jun

Ling

2020

Journal of Control Science and Engineering

View full text Add to dashboard Cite

In this paper, a hybrid fault-tolerant control method with off-line design and online scheduling is proposed for NCS with actuator faults, random delay, and external finite energy disturbance. The problem of less conservatism of robust generalized H2/H∞ hybrid fault-tolerant control is studied. Firstly, a closed-loop fault model of the system with random delay parameters was established according to the Bernoulli 0-1 distribution; all possible prior faults are divided into a few intervals according to certain rules, and then an interval fault-tolerant controller is designed off-line according to the prior faults of each interval. Secondly, when the fault is estimated online, the corresponding interval fault-tolerant controller is called through the scheduling mechanism to achieve rapid fault tolerance of prior faults within the interval and mitigate the impact of other faults within the interval, which provides a guarantee for subsequent safe reconstruction control. Finally, the effectiveness of the proposed method is verified by Matlab simulation.

show abstract

“…Owing to these issues, the researchers have paid much attention to study the stability problems of dynamic systems with probabilistic delays. For example, in [32], some sufficient conditions have been established to ensure the exponential stability of impulsive systems subject to random delays via the reciprocal convex technique. Furthermore, in [31], both the information of variant range of time delay and the probabilistic characteristic of the timevarying delay have been fully taken into account, and a new delay-dependent stability criterion has been given.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Fault-Tolerant Control for a Class of Uncertain Systems With Probabilistic Random Delays

Zhang

2019

IEEE Access

View full text Add to dashboard Cite

This paper investigates the robust control problem of uncertain nonlinear systems subject to actuator faults via the integral sliding mode control (ISMC) scheme. The actuator failures contain the cases of an outage, loss of effectiveness, and stuck fault, which are frequently encountered in practical applications. Furthermore, in this paper, the time-varying delay considered obeys the probability distribution within certain intervals. By fully considering the information of the probabilistic random delay, new sufficient conditions are given to ensure the asymptotical stability of the controlled system with prescribed H ∞ performance. Moreover, a new control law is proposed to compensate for the effects induced by the actuator faults, and an adaptive mechanism is adapted to estimate the unknown terms. In a word, the proposed ISMC scheme ensures the asymptotical stability with guaranteed H ∞ performance of the closed-loop system and forces that the state trajectories are attracted to the pre-designed sliding surface. Finally, a practical example of the rocket fairing structural acoustic model is used to clarify the validly of the presented control method. INDEX TERMS Networked system, integral sliding mode control, actuator faults, adaptive mechanism, probabilistic random delays.

show abstract

Exponential stability of impulsive systems with random delays under sampled‐data control

Cited by 8 publications

References 40 publications

Exponential and fixed‐time stabilization of memristive neural networks with mixed delays

Exponential and fixed‐time stabilization of memristive neural networks with mixed delays

Hybrid Robust H2/H∞ Fault-Tolerant Control with Random Delay NCS

Adaptive Sliding Mode Fault-Tolerant Control for a Class of Uncertain Systems With Probabilistic Random Delays

Contact Info

Product

Resources

About