sampled-data nonlinear systems 采样数据非线性系统
A stable adaptive control approach using dynamic neural networks has been developed for a class of multi input multi output MIMO sampled data nonlinear systems with unknown dynamic nonlinearities.
研究了一类采样数据非线性系统的动态神经网络稳定自适应控制方法。
In this paper, we mainly study a kind of multirate nonlinear sampled-data control systems, and discuss the stability properties of its solution while its sampler produces quantization during sampling.
本文主要研究一类多步长非线性采样控制系统，探讨系统进行采样过程中产生量化误差的情况下其解的稳定性质。
A sampled-data control system approach is presented to a class of affine nonlinear networked control systems described by a hybrid dynamic system model.
利用采样数字控制系统的方法分析了一类混杂动态系统模型描述的仿射非线性网络控制系统的稳定性问题。
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