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Direct Adaptive Decoupling Control of Nonlinear Systems Based on Neural Networks and Multiple Models

机译:基于神经网络和多模型的非线性系统直接自适应解耦控制

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摘要

A direct adaptive decoupling controller is presented for a class of uncertain nonlinear multivariable discrete time dynamical systems. The direct adaptive decoupling controller is composed of a linear direct adaptive decoupling controller, a neural network nonlinear direct adaptive decoupling controller and a switching mechanism. The linear decoupling controller can provide boundedness of the input and output signals, and the nonlinear decoupling controller can improve performance of the system, while the switching mechanism is utilized to obtain the improved system performance and stability simultaneously. Theory analysis and simulation results are presented to show the effectiveness of the proposed method.
机译:提供了一种直接的自适应解耦控制器,用于一类不确定的非线性多变量离散时间动力系统。直接自适应解耦控制器由线性直接自适应解耦控制器组成,是神经网络非线性直接自适应解耦控制器和切换机构。线性去耦控制器可以提供输入和输出信号的界限,并且非线性去耦控制器可以提高系统的性能,而开关机构用于同时获得改进的系统性能和稳定性。提出了理论分析和仿真结果,以显示了所提出的方法的有效性。

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