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A robust adaptive fuzzy wavelet network based controller for a class of non-linear systems

机译:一类非线性系统的鲁棒自适应模糊小波网络控制器

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This paper deals with the synthesis of an adaptive fuzzy wavelet network (FWN) controller for an nth order multi input multi output (MIMO) non-linear system suffering from parameters uncertainties and subjected to external perturbation. The proposed approach allows combining the advantages of the fuzzy logic system and those of wavelet networks to approximate quickly the unknown system dynamics with neither a prior knowledge about such dynamics nor offline learning phase. The FWN is adjusted online using some adaptation laws deduced from the stability analysis which guarantees a non-singular control action. Furthermore, the robustness of the proposed method is improved such that the knowledge of the upper bounds of both the external disturbances and the approximation errors is not required. Moreover, a variable sliding mode control (VSMC) technique is proposed to reduce the starting energy, caused by the presence of approximations errors and external disturbances, without deteriorating the tracking performances. To ensure the robustness of the overall closed loop system, analytical demonstration using Lyapunov theorem is considered. Finally, a numerical example is presented to validate our approach and to show the fast convergence, good tracking and the robustness of the closed loop system.
机译:本文针对具有参数不确定性并受到外部扰动的n阶多输入多输出(MIMO)非线性系统的自适应模糊小波网络(FWN)控制器进行了综合。所提出的方法允许结合模糊逻辑系统和小波网络的优点来快速估计未知的系统动力学,而既不具有关于这种动力学的先验知识,也不具有离线学习阶段。使用从稳定性分析中得出的一些适应定律,在线调整FWN,以保证非奇异的控制作用。此外,改进了所提出方法的鲁棒性,从而不需要了解外部干扰和近似误差的上限。此外,提出了一种可变滑模控制(VSMC)技术,以减少由于近似误差和外部干扰的存在而引起的启动能量,而不会降低跟踪性能。为了确保整个闭环系统的鲁棒性,考虑使用Lyapunov定理进行分析演示。最后,给出了一个数值示例,以验证我们的方法并显示出闭环系统的快速收敛,良好的跟踪和鲁棒性。

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