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A neural network-based sliding-mode control for rotating stall and surge in axial compressors

机译:基于神经网络的滑模控制,用于轴流压缩机的旋转失速和喘振

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摘要

A decoupled sliding-mode neural network variable-bound control system (DSMNNVB) is proposed to control rotating stall and surge in jet engine compression systems in presence of disturbance and uncertainty. The control objective is to drive the system state to the original equilibrium point and it proves that the control system is asymptotically stable. In this controller, an adaptive neural network (NN) control scheme is employed for unknown dynamic of nonlinear plant without using a model of the plant. Moreover, no prior knowledge of the plant is assumed. The proposed DSMNNVB controller ensures Lyapunov stability of the nonlinear dynamic of the system.
机译:提出了一种解耦滑模神经网络可变边界控制系统(DSMNNVB),用于在存在干扰和不确定性的情况下控制喷气发动机压缩系统的旋转失速和喘振。控制目标是将系统状态驱动到原始平衡点,并证明控制系统是渐近稳定的。在该控制器中,对非线性植物的未知动态采用了自适应神经网络(NN)控制方案,而无需使用植物模型。而且,不假定对植物有先验知识。所提出的DSMNNVB控制器可确保系统非线性动力学的Lyapunov稳定性。

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