Event‐triggered integral sliding mode control for fractional order T‐S fuzzy systems via a fuzzy error function

Abstract

This article considers the event-triggered integral sliding mode control problem for fractional order T-S fuzzy systems. A fuzzy error function and a mixed triggering threshold are proposed to design the event-triggering mechanism, in which the fuzzy error function is used to design the triggering function. The mixed triggering threshold is composed of the time-varying threshold with power function and the fixed one. Based on the proposed fuzzy error function, the boundedness of sliding variable errors can be guaranteed by using the time-varying threshold with power function. Meanwhile, the fixed threshold is used to adjust the value of mixed triggering threshold near the initial time. Furthermore, a sufficient condition on the asymptotical stability for sliding motion is established and a positive internal execution time can be ensured. At last, two simulation examples are presented to illustrate the effectiveness of obtained theoretical results.

Output feedback control for uncertain fractional-order system subject to deception cyber-attacks via observer-based event-triggered scheme 1

“…Remark 3.1. To illustrate the randomness of deception attacks, introduce a stochastic variable β(ℵ), γ(ℵ) that obeys the Bernoulli distribution, as given in (13). There are two major scenarios discussed in (5), that is (1).…”

Hybrid‐driven‐based resilient control for networked T‐S fuzzy systems with time‐delay and cyber‐attacks

“…Therefore, based on fuzzy set theory T-S fuzzy system is a impressive device to handle such nonlinearities in NCSs. [29][30][31][32] Under T-S fuzzy strategy, complex nonlinear plants can be observed as a total consolidation of linear subsystems subject to membership functions, and can be dealt through the same way of linear system theory. 33 Therefore, the problems of networked T-S fuzzy systems with hybrid-driven mechanism are important in recent years.…”

“…On the other hand, Takagi–Sugeno (T‐S) fuzzy model is first constructed in Reference 28 and afterwards much attention have been paid in the filter design, stability and stabilization for fuzzy systems over the past many years. Therefore, based on fuzzy set theory T‐S fuzzy system is a impressive device to handle such nonlinearities in NCSs 29‐32 . Under T‐S fuzzy strategy, complex nonlinear plants can be observed as a total consolidation of linear subsystems subject to membership functions, and can be dealt through the same way of linear system theory 33 .…”

Stability of nonlinear distributed delay system with parameter uncertainties: Integral‐based event‐triggered impulsive control strategy

“…28,29 Recently, event-triggered control scheme has been developed to cope with the disadvantages of sampling data control, in which the samples are transmitted by the sensor only when a predefined condition is satisfied. 7,[30][31][32][33][34][35][36][37][38] The predefined event-triggered strategy is often related to the current system states information, which allows signal exchange to be smartly allocated according to the "need" of the controlled plant. In this way, the communication resources over the network can be largely saved.…”