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基于动态神经网络，研究了一类具有未建模动态的未知多变量非线性系统的鲁棒直接自适应控制．基于Ｌｙａｐｕｎｏｖ理论得出一种鲁棒稳定的权学习算法，该算法不需要知道理想权矩阵的先验知识，并保证设计的控制器的稳定性．仿真结果表明提出的鲁棒控制算法的有效性
Based on the dynamic neural network, a robust direct adaptive control of a class of unknown multivariable nonlinear systems with unmodeled dynamics is studied. Based on Lyapunov theory, a robust and stable weight learning algorithm is obtained, which does not need to know the prior knowledge of the ideal weight matrix and ensure the stability of the designed controller. Simulation results show the effectiveness of the proposed robust control algorithm