Optimal control for uncertain discrete-time singular systems under expected value criterion

Shu, Yadong; Li, Bo; Zhu, Yuanguo

doi:10.1007/s10700-020-09346-5

Cited by 4 publications

(1 citation statement)

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“…However, due to the inherent delay in the networked control system, it is difficult to achieve the exact tracking for the nonlinear system. So this problem can be investigated further for the exact output regulation by using the optimal control [40], adaptive control [27], and neural network [11]. Remark 4.2.…”

Section: Exosystem In Linear For Fuzzy Regulationmentioning

confidence: 99%

Output regulation for time–delayed Takagi–Sugeno fuzzy model with networked control system

Aslam

2023

Hacettepe Journal of Mathematics and Statistics

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This article studies H∞ control problem based on the event–triggered scheme with time delays for the synchronization of an chaotic system represented by delayed Takagi–Sugeno models. Firstly, this method depending on two scenarios: a) Each local subsystem in- tegrated that the delayed T–S fuzzy model for the same value of input matrices for the networked system and b) This is near steady-state zero-error diversification has to all be the same local subsystems. Generally, in the case of fuzzy regulation, these in lieu of generating the fuzzy regulator as a result of linear local controllers, circumstances were adjusted by addressing the issue of fuzzy regulation for the delayed Takagi–Sugeno models fuzzy model. Then, a delayed Takagi–Sugeno uses a fuzzy system to model the non–linear regulator. On the other hand, communication delays are a vital factor that cannot be ig- nored. To tackle the networked induced delay initially, author attempt to implement the event–triggered scheme for output regulation which reduce the cost of network transmis- sion. By constructing a Lyapunov functional and making use of event–triggered method, some suitable circumstances that ensure asymptotic stability of H∞ performance index for the resulting model were derived. Additionally, as the variations of the aforementioned results, two scenarios were presented. Our developed approaches are demonstrated by a final example illustrating their superiority, usefulness and reliability.

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Section: Exosystem In Linear For Fuzzy Regulationmentioning

confidence: 99%