On the stability of fuzzy chaotic systems based on linear matrix inequalities LMI

Gam, Rihab; Sakly, Anis

doi:10.1109/icosc.2016.7507041

Cited by 2 publications

(3 citation statements)

References 15 publications

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“…Therefore, we utilize Theorem 1 such that the stability of the quasilinearization of the chaos system is globally stable with H ∞ performance. Since the chaos discrepancy system (29) is a special polynomial fuzzy system (i = 1), the stability conditions with H ∞ performance (12) of Theorem 1 can be simplified as…”

Section: Casementioning

confidence: 99%

“…Furthermore, solving LMI-based stability conditions can secure the state feedback gain. Thus, chaotic systems have been synchronized through T-S fuzzy modeling and control [9][10][11][12]. In [9], the LMI-based fuzzy control was applied to synchronization of chaotic systems.…”

Section: Introductionmentioning

confidence: 99%

“…In [11], the design of an adaptive TSK fuzzy self-organizing compensator was proposed for chaotic systems. An exact linearization (EL) technique, which was employed to synchronize the chaotic systems via the PDC, has been discussed [12]. However, there still exist two design issues in LMI-based T-S fuzzy control methodology.…”

Section: Introductionmentioning

confidence: 99%

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Synthesis of Polynomial Fuzzy Model-Based Designs with Synchronization and Secure Communications for Chaos Systems with H∞ Performance

Chang

2021

Processes

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This paper presents the sum of squares (SOS)-based fuzzy control with H∞ performance for a synchronized chaos system and secure communications. To diminish the influence of the extrinsic perturbation, SOS-based stability criteria of the polynomial fuzzy system are derived by using the polynomial Lyapunov function. The perturbation decreasing achievement is indexed in a H∞ criterion. The submitted SOS-based stability criteria are more relaxed than the existing linear matrix inequality (LMI)-based stability criteria. The cryptography scheme based on an n-shift cipher is combined with synchronization for secure communications. Finally, numerical simulations illustrate the perturbation decay accomplishment of the submitted polynomial fuzzy compensator.

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Section: Casementioning

confidence: 99%