The APPliCation of Fuzzy Neural Network Control in the AC Speed Adjustment System

2012 ◽  
Vol 487 ◽  
pp. 166-170
Author(s):  
Yan Lei Jiang ◽  
Han Lian
Keyword(s):  
Network Control ◽  
Simulation Research ◽  
Object A ◽  
Self Study ◽  
Fuzzy Neural ◽  
Adjustment System ◽  
Fuzzy Network ◽  
Speed Adjustment ◽  
Research Show ◽  
Controlled Object

This paper investigates the complex controlled object. A method of fuzzy-network is proposed. Results of simulation research show that the controller has not only high self-study ability, but also high robustness, and let the performance in AC speed adjustment system quickly improve.

Research of Power Plant Boiler Control System Based on Compensatory Fuzzy Neural Network

2014 ◽  
Vol 614 ◽  
pp. 203-206 ◽  
Author(s):  
Guo Qiang Hou ◽  
Wei Jie Zhao ◽  
Si Lan Li
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Fuzzy Neural Network ◽  
Fuzzy Inference ◽  
Thermal Power ◽  
Network Control ◽  
Neural Network Control ◽  
Simulation Tools ◽  
Fuzzy Neural ◽  
Fuzzy Network

Considering thermal power plant boiler’s nonlinear, large delay and time-varying, the paper proposes a compensatory fuzzy neural network control based on fuzzy control and neural network control. The compensatory fuzzy neural network is better than the PID controller and general fuzzy network controller in properties by using fuzzy inference and compensatory arithmetic. The paper makes a preliminary simulation using simulation tools of Matlab. And, the superiority of the compensatory fuzzy neural network control is proved by comparing the two kinds of simulation.

The Simulation Study for Auto Electrical Seat Controller Based on Fuzzy Control Technology

2011 ◽  
Vol 383-390 ◽  
pp. 7328-7331
Author(s):  
Lan Jiang Zhang ◽  
Gui Jie Wang
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Effective Means ◽  
Nonlinear Function ◽  
Control Technology ◽  
Highly Nonlinear ◽  
Adjustment System ◽  
The Mathematical Model ◽  
Seat Adjustment ◽  
Controlled Object

Designed the control system policy for automobile electric seat using fuzzy control technology, therefore established its control model by Fuzzy Logic Toolbox, and carried on the off-line simulation to choose controller's optimum control parameters. From the dynamic viewpoint, the auto electric seat adjustment system is not only a complex nonlinear function which includes the location of the DC servo motor and the speed, but also contains serious nonlinear coupling interference, so the system is a highly nonlinear strong coupling, variable multivariable system. Application of traditional control methods (such as traditional PID) is difficult to meet its order requirements, so the research is highly robust method of intelligent control is an effective way to solve the problem. Fuzzy control technology has become the field in which drawn greater attention and researched in recent years. It doesn’t depend on the mathematical model of controlled object, has a good robustness, and nonlinear control characteristics, so it is an effective means to control the object with time-varying, non- linear parameters. In this paper, fuzzy control technology to achieve the orders of auto electric seat adjustment control system functions in the Literature [1], and the tracking of the system was simulated.

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