A new approach to dynamical system's fuzzy controller synthesis: Application of the unstable subsystem

2017 ◽  
Author(s):  
L. Demkiv ◽  
A. Lozynskyy ◽  
O. Lozynskyy ◽  
I. Demkiv
Keyword(s):  
Fuzzy Controller ◽  
Controller Synthesis ◽  
New Approach ◽  
Unstable Subsystem

scholarly journals Fuzzy logic for control Peltier module

2018 ◽  
Vol 19 (6) ◽  
pp. 704-707
Author(s):  
Emil Sadowski ◽  
Tomasz Marek ◽  
Roman Pniewski ◽  
Rafał Kowalik
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Control Process ◽  
Controller Synthesis ◽  
Cell Control ◽  
Control Value ◽  
Peltier Module ◽  
Current Value

The article presents the Peltier cell control system devel-oped by the authors. Due to the non-linear dependence of the cell's efficiency on the current, fuzzy logic was used to determine the control value. In the following parts of the article the actual characteristics of the Peltier cells, the method of determining the control current value (fuzzy controller synthesis). The controller of fuzzy logic and its relation to traditional control in a closed system and obtained results have been presented. The FUDGE software from Motorola was used to implement fuzzy logic. The control algorithm presented in the article will be used to develop cell control system that enables optimization of the Peltier cell control process.

A FUZZY CONTROLLER SYNTHESIS FOR A BOOST CONVERTER

2005 ◽  
Vol 38 (1) ◽  
pp. 181-186 ◽  
Author(s):  
Kamel Guesmi ◽  
Najib Essounbouli ◽  
Abdelaziz Hamzaoui ◽  
Noureddine Manamanni ◽  
Janan Zaytoon
Keyword(s):  
Fuzzy Controller ◽  
Boost Converter ◽  
Controller Synthesis

Online Prediction Control Model of CO2 Concentration for Pleurotus eryngii in the Sporocarp Period Based on Matlab and LabVIEW

2017 ◽  
Vol 868 ◽  
pp. 45-50
Author(s):  
Xiao Qing Tian ◽  
Kang Zhang ◽  
Nan Bai ◽  
Xue Jun Zhu
Keyword(s):  
Prediction Model ◽  
Fuzzy Controller ◽  
Forecast Model ◽  
Pleurotus Eryngii ◽  
Time Varying ◽  
Prediction System ◽  
New Approach ◽  
Cultivation Process ◽  
Prediction Control ◽  
Favorable Conditions

In the industrialized cultivation process of fungi, CO2 concentration control system is a nonlinear, time-delay and time-varying system, which is difficult to establish a precise mathematical model. Considering the situation, CO2 concentration prediction model that based on neural network was built, and a fuzzy controller was proposed further based on the prediction model. Finally, matlab/labview based online forecast model was finished, and it is verified that the prediction system has higher prediction accuracy with robust character. It also provides a new approach to control key environmental factors under more favorable conditions for mushroom growth.

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