Projective synchronization of nonidentical fractional-order neural networks based on sliding mode controller
This paper investigates global projective synchronization of nonidentical fractional-order neural networks (FNNs) based on sliding mode control technique. We firstly construct a fractional-order integral sliding surface. Then, according to the sliding mode control theory, we design a sliding mode co...
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| Veröffentlicht in: | Neural networks 2016-04, Vol.76, p.97-105 |
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| container_title | Neural networks |
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| creator | Ding, Zhixia Shen, Yi |
| description | This paper investigates global projective synchronization of nonidentical fractional-order neural networks (FNNs) based on sliding mode control technique. We firstly construct a fractional-order integral sliding surface. Then, according to the sliding mode control theory, we design a sliding mode controller to guarantee the occurrence of the sliding motion. Based on fractional Lyapunov direct methods, system trajectories are driven to the proposed sliding surface and remain on it evermore, and some novel criteria are obtained to realize global projective synchronization of nonidentical FNNs. As the special cases, some sufficient conditions are given to ensure projective synchronization of identical FNNs, complete synchronization of nonidentical FNNs and anti-synchronization of nonidentical FNNs. Finally, one numerical example is given to demonstrate the effectiveness of the obtained results. |
| doi_str_mv | 10.1016/j.neunet.2016.01.006 |
| format | Article |
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| ispartof | Neural networks, 2016-04, Vol.76, p.97-105 |
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| language | eng |
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| source | Elsevier ScienceDirect Journals Complete - AutoHoldings; MEDLINE |
| subjects | Algorithms Controllers Design engineering Fractional-order integral sliding surface Fractional-order neural networks Neural networks Neural Networks (Computer) Projective synchronization Sliding Sliding mode Sliding mode control Sliding mode controller Synchronism Synchronization |
| title | Projective synchronization of nonidentical fractional-order neural networks based on sliding mode controller |
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