This paper presents an iterative algorithm of optimal control for discrete time nonlinear systems, according to the differences of the real system and its bilinear model.
针对双线性模型与实际系统之间的差异，提出一种基于双线性模型求解非线性动态系统最优控制的迭代算法。
A real time modeling approach for nonlinear discrete time system is presented by using the concept of time variant recurrent neural network and the theory of two dimensional system.
利用时变反馈神经网络的概念及二维线性系统理论给出了非线性离散系统的一种实时建模方法。
A multiple models neural network decoupling controller is designed to control the multivariable nonlinear discrete time system.
针对多变量非线性离散时间系统设计多模型神经网络解耦控制器。
The main result is that a discrete time minimum phase nonlinear system is stabilizable via dynamic output feedback if its zero dynamics is approximately asymptotically stable.
主要结果是，如果一非线性系统的零动态是逼近渐近稳定的，则能用动态输出反馈镇定。
The paper presents a linear algebraic solution of the dynamic disturbance decoupling problem for a generalized discrete time nonlinear system.
提供了离散时间广义非线性控制系统的不可测扰动的一种‘反演算法’。
A multiple model based generalized predictive control is provided for complex nonlinear discrete time system.
对于复杂的离散时间非线性系统，提出一种基于多模型的广义预测控制方法。
Aimed at the problem of iterative learning control for nonlinear discrete time-variant system, the improved iterative learning control algorithm is given.
针对非线性离散时变系统的迭代学习控制问题，提出了一种改进的迭代学习控制算法。
The lab has ten experiments, covering time and frequency domain analysis of linear system, root locus and series compensation of linear system, analysis of discrete and nonlinear system.
本虚拟实验室共设计了十个实验，内容涉及线性系统时域分析、线性系统的根轨迹、线性系统频域分析、线性系统串联校正、离散系统分析和非线性系统分析。
Then, aimed at the problem of iterative learning control for nonlinear discrete time-variant system, the improved iterative learning control algorithm was given in the paper.
然后，文章针对非线性离散时变系统的迭代学习控制问题，提出了一种改进的迭代学习控制算法。
For nonlinear discrete systems, the T-S model is constructed and the parametric uncertainty and time-delay terms are introduced to make the fuzzy model approach to the original system more exactly.
针对非线性离散系统，构造t - S模型，引入参数不确定项和时滞项，使得模糊模型能够更精确逼近原系统。
For nonlinear discrete systems, the T-S model is constructed and the parametric uncertainty and time-delay terms are introduced to make the fuzzy model approach to the original system more exactly.
针对非线性离散系统，构造t - S模型，引入参数不确定项和时滞项，使得模糊模型能够更精确逼近原系统。
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