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A hyperstable neural network for the modelling and control on nonlinear systems

机译:用于非线性系统建模和控制的超稳定神经网络

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摘要

A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given.
机译:提出了一种基于神经网络的多变量超稳定鲁棒自适应解耦控制算法,用于控制未知参数和结构的非线性多变量耦合系统。 Popov定理用于控制器的设计。通过神经网络在线识别系统的建模误差,耦合作用和其他不确定性。所识别的结果被用作补偿信号,从而实现了非线性系统的鲁棒自适应控制。给出了仿真结果。

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