This paper investigates the problem of the model validation in identifying discrete-time-nonlinear dynamic systems by using neural networks with a single hidden layer.
讨论了利用仅含一个隐层的前馈多层神经网络来辨识离散时间非线性动态系统时的模型检验问题。
Based on the approximation capability of fuzzy logic systems, a design method of an adaptive fuzzy logic controller is given for a class of nonlinear discrete time systems.
针对一类非线性离散时间系统，根据模糊逻辑系统的逼近性质，给出了一种自适应模糊逻辑控制器的设计方法。
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。
Developed in this paper are fuzzy decentralized state feedback and observer-based decentralized output feedback controllers for a class of discrete nonlinear interconnected systems with time-delay.
本文对一类离散非线性互联时滞系统，给出了模糊分散状态反馈和基于观测器的分散输出反馈模糊控制方法。
Then stability of linear and nonlinear time-varying discrete large scale systems is studied respectively when their isolated subsystems satisfy the above condition.
然后研究当孤立子系统满足上述条件时的线性及非线性时变离散大系统的稳定性。
A multi layer fuzzy CMAC adaptive control method based on an approximate model is presented in this paper for nonlinear discrete time systems.
针对非线性离散时间系统的控制问题，提出了一种基于近似模型的多层模糊CMAC自适应控制方法。
The exact linearization of a class of implicit discrete-time nonlinear singular systems is studied.
讨论隐含离散时间奇异非线性系统的精确线性化问题。
A direct adaptive control approach is proposed for a class of uncertain discrete time nonlinear non-minimum phase dynamical systems.
针对一类不确定的离散时间非线性非最小相位动态系统，提出了一种基于神经网络和多模型的直接自适应控制方法。
The paper investigates the guaranteed cost control problem for a class of uncertain nonlinear discrete time-delay 2d systems.
本文针对一类不确定非线性离散时滞2d系统，研究其保性能控制器设计问题。
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。
应用推荐