Intelligent automatic landing system using time delay neural network controller

2003 ◽  
Vol 17 (7) ◽  
pp. 563-581 ◽  
Author(s):  
Jih-gau Juang ◽  
Hao-Hsiang Chang ◽  
Wu-Ben Chang
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Neural Network Controller ◽  
Network Controller ◽  
Automatic Landing

Neural Network Control for Uncertain Nonlinear Time-Delay Systems

2014 ◽  
Vol 898 ◽  
pp. 705-708
Author(s):  
Hong Yu Gao ◽  
Xiu Ming Wang ◽  
Yuan Gao ◽  
Ke Yong Shao
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Nonlinear Function ◽  
Network Control ◽  
Delay Systems ◽  
Time Delay Systems ◽  
Neural Network Controller ◽  
Network Controller

Based on stability theory, a class of neural network controller design of uncertain nonlinear time-delay systems is studied. Using the ability that neural network can approximate any nonlinear function, a kind of weights correction law based on radial basis function (RBF) neural network (NN) and the adaptive controller design scheme are proposed. According to Lyapunov stability analysis method, this paper gives the sufficient conditions that neural network controller can make this kind of uncertain nonlinear time-delay systems stable in the sense of Lyapunov. At last, the proposed neural network controller is verified to be correct and effective by the simulation examples.

Research on Intelligent Variable Frequency of Air-Conditioner Control System Based on Fuzzy Control

2011 ◽  
Vol 110-116 ◽  
pp. 4076-4084
Author(s):  
Hai Cun Du
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Neural Network ◽  
Air Conditioner ◽  
Neural Network Controller ◽  
The Neural Network ◽  
Network Controller ◽  
Fuzzy Neural ◽  
Fuzzy Control Strategy

In this paper, we determine the fuzzy control strategy of inverter air conditioner, the fuzzy control model structure, the neural network and fuzzy control technology, structural design of the fuzzy neural network controller as well as the neural network predictor FNNC NNP. Simulation results show that the fuzzy neural network controller can control the accuracy greatly improved the compressor, and the control system has strong adaptability to achieve a truly intelligent; model of the controller design and implementation of technology are mainly from the practical point of view, which is practical and feasible.

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