研究了一类具有未知常数控制增益的耦合大系统的直接自适应神经网络控制问题。
The problem of direct adaptive neural network control for a class of interconnected systems with unknown constant control gains is studied in this paper.
研究了一类具有未知常数控制增益的MIMO非线性系统的自适应模糊控制问题。
The problem of adaptive fuzzy control for a class of MIMO nonlinear systems with unknown constant control gains is studied in this paper.
针对控制增益为未知常数和未知函数两种情形，分别提出分散自适应滑模控制器设计新方案。
Considering two cases that the system has constant control gains or function control gams, two novel decentralized adaptive sliding mode control schemes are presented, respectively.
提出了一种k-均值聚类算法和SOM自组织神经网络算法相结合的异常检测模型，使得系统可以更好的分类正常数据流和异常数据流，以此来防范未知的攻击。
Secondly, the anomaly detection model based on K-means algorithm and SOM network is constructed. It can classify the normal and abnormal network data stream so better to detect the unknown attack.
提出了一种k-均值聚类算法和SOM自组织神经网络算法相结合的异常检测模型，使得系统可以更好的分类正常数据流和异常数据流，以此来防范未知的攻击。
Secondly, the anomaly detection model based on K-means algorithm and SOM network is constructed. It can classify the normal and abnormal network data stream so better to detect the unknown attack.
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