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Interval type-2 fuzzy control for nonlinear system via adaptive memory-event-triggered mechanism

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Abstract

This article focuses on the issue of adaptive memory-event-triggered control for a class of interval type-2 Takagi–Sugeno fuzzy system (IT-2 TSFS) subjected to network-induced delays. Firstly, the IT-2 TSFS is established to effectively describe the nonlinearities and parameter uncertainties. Secondly, in order to decrease the burden of network transmission, a novel adaptive memory-event-triggered mechanism (AMETM) is presented by employing a buffer in event-triggered module. The historical information stored in the buffer is used to select the “necessary” control signal. Furthermore, the proposed AMETM can adaptively adjust the threshold to balance the data releasing rate and control performance. Then, the stability analysis is carried out by utilizing the discontinuous looped Lyapunov–Krasovskii functional. The properties of fuzzy membership functions are used to derive the improved stability conditions, which ensure the \(H_{\infty }\) performance. Finally, the numerical example is represented to verify the advantages of the control method.

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Authors and Affiliations

  1. North China University of Science and Technology, Tangshan, China

    Chao Ge, Chengyuan Liu, Yajuan Liu & Changchun Hua

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  1. Chao Ge
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  2. Chengyuan Liu
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Ge, C., Liu, C., Liu, Y. et al. Interval type-2 fuzzy control for nonlinear system via adaptive memory-event-triggered mechanism. Nonlinear Dyn 111, 1301–1314 (2023). https://doi.org/10.1007/s11071-022-07880-y

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