Sliding-Mode Control for IT2 Fuzzy Nonlinear Singularly Perturbed Systems and Its Application to Electric Circuits: A Dynamic Event-Triggered Mechanism

Shen, Hao; Yuan, Linhong; Wang, Jing; Yan, Huaicheng; Chadli, Mohammed

doi:10.1109/tsmc.2023.3240994

Cited by 12 publications

(2 citation statements)

References 42 publications

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“…As, e(k) = e 1 (k) + e 2 (k), therefore taking norm on both sides, it satisfies ||e(k (15), one can write as ||e(k)|| ≤ 𝜎(a 0 + c k 1 ). Substituting this in the above argument (44), we obtain ΔV(z) ≤ −…”

Section: δV = (Mz(k) + Be(k) + H) T P(mz(k)mentioning

confidence: 97%

“…Therefore, in this work, we consider the reduction of network resources by separating the updates of slow and fast components of control and avoiding redundant control updates by using an input-based error in the triggered condition. A few applications of SPSs can be found in [44][45][46][47] and the references therein. Based on the above observations, we propose the input-based stabilized ETM for discrete-time SPS to deal with constrained network resources.…”

Section: Introductionmentioning

confidence: 99%

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Input‐based event‐triggered control of a discrete‐time singularly perturbed system under a resource constrained environment

Sahu

Bhandari

Fulwani

2023

Asian Journal of Control

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This paper proposes an input‐based event‐triggered mechanism for a network‐controlled discrete‐time singularly perturbed system, where the latest measurements are transmitted when a predefined condition is satisfied on the input. The significant contribution of the proposed work is the separation of control updates for slow and fast dynamics such that the proposed event‐triggered mechanism updates and broadcasts the current measurements of slow and fast dynamics in their respective time scales and reduces the usage of network resources. Further, the proposed input‐based event‐triggered mechanism avoids redundant updates of the control input and reduces actuation and resource utilization in some instances. Furthermore, the ultimate boundedness of the system states is established. The simulation uses a quarter‐car suspension system to demonstrate the proposed theory.

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Section: δV = (Mz(k) + Be(k) + H) T P(mz(k)mentioning

confidence: 97%