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首页> 外文期刊>International journal of machine learning and cybernetics >Projective synchronization for two nonidentical time-delayed fractional-order T-S fuzzy neural networks based on mixed H_∞/passive adaptive sliding mode control
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Projective synchronization for two nonidentical time-delayed fractional-order T-S fuzzy neural networks based on mixed H_∞/passive adaptive sliding mode control

机译:基于混合H_∞/被动自适应滑模控制的两个时滞分数阶T-S模糊神经网络的投影同步

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摘要

This paper deals with the problem of mixed H/passive projective synchronization for two different fractional-order (FO) T-S fuzzy neural networks with uncertain parameters and time delays. Firstly, a fractional integral sliding surface which is suitable for the considered FO error system is proposed. Second, in terms of the established sliding surface, combining a novel reaching law, a new adaptive sliding mode control law is introduced, which can force the closed-loop dynamic error system trajectories to reach the sliding surface. Then, by giving a continuous frequency distributed model of the FO dynamic networks and the application of FO system stability theory, the projective synchronization conditions are addressed in terms of linear matrix inequality techniques. Based on the conditions, a desired controller which can guarantee the robust stability of the closed-loop system and also ensure a mixed H/passive performance level is designed. Finally, synchronization of two nonidentical time-delayed FO T-S fuzzy neural networks with uncertain parameters as a simulation example is given to illustrate the effectiveness of the proposed method.
机译:针对具有不确定参数和时滞的两个不同分数阶(FO)T-S模糊神经网络,研究了混合H /被动投影同步问题。首先,提出了适合于所考虑的FO误差系统的分数整体滑动表面。其次,针对已建立的滑动面,结合一种新颖的到达定律,引入了一种新的自适应滑模控制律,它可以迫使闭环动态误差系统的轨迹到达滑动面。然后,通过给出FO动态网络的连续频率分布模型和FO系统稳定性理论的应用,利用线性矩阵不等式技术解决了投影同步条件。根据这些条件,设计了一种既能保证闭环系统鲁棒稳定性又能确保混合的H /被动性能水平的控制器。最后,以两个具有不确定参数的不相同时滞的FO T-S模糊神经网络的同步为仿真实例,说明了该方法的有效性。

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