Event-triggered H∞ anti-synchronisation for delayed neural networks with discontinuous neuron activations via non-fragile control strategy. Issue 4 (2nd October 2019)

• Record Type: Journal Article
• Authors: Liu, Min; Wu, Huaiqin; Cao, Jinde; Wang, Yanning
• Is Part Of: Connection science. Volume 31:Issue 4(2019)
• Page Start: 373
• Page End: 429
• Publication Date: 2019-10-02
• Subjects: Discontinuous neural networks -- non-fragile anti-synchronisation -- H∞ anti-synchronisation -- mixed time-varying delays -- event-triggered control scheme -- Wiritinger-based multiple integral inequality; Neural computers -- Periodicals; Artificial intelligence -- Periodicals; Cognitive science -- Periodicals; Connectionism -- Periodicals; 006.3
• DOI: 10.1080/09540091.2019.1604628
• Languages: English
• ISSNs: 0954-0091

Abstract

Abstract : This paper treats of the global event-triggered anti-synchronisation issue for discontinuous neural networks with the mixed time-varying delays and random feedback gain fluctuation via non-fragile control strategy. The random gain uncertainties are described by stochastic variables satisfying the Bernoulli distribution. Firstly, the novel hybrid controllers, which are composed of the non-fragile controller and the event-triggered controller, are designed. Then, based on Clarke's non-smooth analysis theory, general free-weighting matrix method, the Lyapunov-Krasovskii functional approach and Wirtinger-based multiple integral inequality analysis technology, the global event-triggered non-fragile anti-synchronisation conditions are established in terms of linear matrix inequalities (LMIs). In addition, under the considered external disturbance, the conditions with respect to the global event-triggered non-fragile H ∞ anti-synchronisation are also addressed in forms of LMIs. Finally, two illustrative examples are provided to verify the effectiveness of the designed event-triggered non-fragile control scheme and the validity of theoretical results.