An exponential stabilization criterion for switched delayed interval type-2 fuzzy systems under admissible edge-dependent average dwell time mechanism

Aravind, R. Vijay; Balasubramaniam, P.

doi:10.1016/j.ins.2021.12.082

Cited by 16 publications

(3 citation statements)

References 42 publications

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“…Switched systems can not only solve the fundamental issues in practice, but also enhance the temporary features of systems, so many scholars are absorbed in studying the relevant problems of switched systems (Aravind and Balasubramaniam, 2022; Huang et al, 2020; Lin and Chen, 2021; Sun et al, 2004; Wang et al, 2016, 2021, 2022; Yang et al, 2022; Zhao and Hill, 2008). However, most papers are about linear time invariant (LTI) systems, such as Ma et al (2017) and Yuan and Wu (2015).…”

Section: Introductionmentioning

confidence: 99%

Observer-based event-triggered control for continuous-time switched linear parameter-varying systems

Wang

2023

Transactions of the Institute of Measurement and Control

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This paper researches the interval observer–based event-triggered control of switched linear parameter-varying (LPV) systems, which involve unknown external disturbance and measurement noise. First, we offer an event-triggering condition and a controller which are correlated with state estimations. Then, by analyzing the relationship between switching sequences and sampling sequences, we model the resulting systems as switched time-delay systems. It deserves to note that the mismatches of the switching signal for the controllers and the systems may occur due to the sampling of switching signal. Using the merging switching signal technique and the multiple Lyapunov–Krasovskii functional method, and thinking over both synchronous and asynchronous switching of the systems and the controllers, we acquire relevant conditions which are used to realize the stability of the whole switched LPV closed-loop systems under the mode-dependent average dwell time (MDADT) switching. Next, we give a specific algorithm to design the controller gains. Finally, a numerical example is provided to verify the superiority of the outcomes.

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Section: Introductionmentioning

confidence: 99%

Observer-based event-triggered control for continuous-time switched linear parameter-varying systems

Wang

2023

Transactions of the Institute of Measurement and Control

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“…(15) For nonlinear systems with uncertainties, a Type-2 fuzzyneural network (T2FNN) with Petri networks and a novel universal approximator was proposed, and an interval T2FNN (IT2FNN) with a new robust and adaptive control mechanism was constructed. (16,17) In uncertain nonlinear systems with sector dead zone nonlinearities, a sliding mode controller was presented to ensure the reaching condition. (18) However, there is a need to stabilize the nonlinear system with dead zone nonlinearities, particularly when high-precision movement is required.…”

Section: Introductionmentioning

confidence: 99%

“…By using the proper Lyapunov criterion and Riccati inequality, the SISO nonlinear system also reduces sectorial dead zone nonlinearities, uncertainties, and external disturbances and shows swift H ∞ tracking responses, resilience, and efficacy. (11,12,14,17,18,20,27)…”

Section: Introductionmentioning

confidence: 99%

Adaptive Tracking Control of Single Input Single Output Nonlinear System with Sectorial Dead Zone Using Interval Type-2 Neural Network Fuzzy Control

Chen¹,

Yu²,

Lan³

2023

Sensors and Materials

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Single-input, single-output (SISO) nonlinear systems have problems with sectorial dead zone nonlinearities, noise, uncertainties, approximation errors, and external disturbances. Therefore, we developed an interval Type-2 neural network fuzzy adaptive controller (IT2-NNFAC) for satisfactory H-infinity (H ∞ ) tracking performance to solve the problems of the SISO system. To adjust the parameters of the proposed IT2-NNFAC, a structure of the fuzzy logic inference system and online adaptive laws are adopted, which are based on the Lyapunov stability criterion and Riccati inequality. All systems with the proposed IT2-NNFAC attenuate the effect of external disturbances on tracking errors at any specified level. In the proposed IT2-NNFAC, all the signals in the closed-loop system guarantee uniform and ultimate boundedness and satisfactory tracking performance with the proper Lyapunov stability criterion and Riccati inequality. H ∞ tracking responses and the resilience and efficacy of the proposed IT2-NNFAC were proved by testing a mass spring damper system with sectorial dead zone nonlinearities, uncertainties, and external disturbances.

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Stability criteria for memristor-based delayed fractional-order Cohen–Grossberg neural networks with uncertainties

Aravind

Balasubramaniam

2023

Journal of Computational and Applied Mathematics

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An exponential stabilization criterion for switched delayed interval type-2 fuzzy systems under admissible edge-dependent average dwell time mechanism

Cited by 16 publications

References 42 publications

Observer-based event-triggered control for continuous-time switched linear parameter-varying systems

Observer-based event-triggered control for continuous-time switched linear parameter-varying systems

Adaptive Tracking Control of Single Input Single Output Nonlinear System with Sectorial Dead Zone Using Interval Type-2 Neural Network Fuzzy Control

Stability criteria for memristor-based delayed fractional-order Cohen–Grossberg neural networks with uncertainties

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