非线性系统的模型参考神经网络控制
MODEL REFERENCE NEURAL NETWORK CONTROL FOR NONLINEAR SYSTEM
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摘要: 提出了一种未知非线性动力学系统的神经网络控制策略，用动态多层BP网进行辨识，静态网进行控制．控制器结构简单，收敛快，泛化能力强．仿真结果表明，该策略对几类非线性系统的控制是有效的，且适用于多值逆映射非线性系统，可用于实时控制．Abstract: In this paper, a new neural network control strategy is proposed for unknown nonlinear dynamical systems, using dynamical multilayered BP network to identify and still network to control.The controller has simple substruct, better convergence and stronger extensive ability.Simulation shows the control strategy is effective for several typical nonlinear systems and adaptive for multivalued counter reflection systems, and can be used in realtime online control.
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