In this paper, direct adaptive neural network control is studied for a class of multi-input and multi-output (MEMO) nonlinear systems based on input-output model with unknown inter connections between subsystems. The proposed adaptive algorithm is very simple and easy to implement. By finding a unitary orthogonal matrix to tune the NN weights, the closed-loop system is proved to be semi-globally uniformly ultimately bounded (SGUUB). The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.
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机译：本文研究了基于输入输出模型的一类多输入和多输出（备注）非线性系统的直接自适应神经网络控制。所提出的自适应算法非常简单且易于实现。通过找到单一正交矩阵来调谐NN重量，证明了闭环系统是半全球均匀的最终限定（SGUUB）。 The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.
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