Self Tuning Based Adaptive Fuzzy Logic Controller in Lab view for Sterilizing Equipments

Author(s):  
P. J. Ragu

In this paper, temperature monitoring of sterilizing equipment system was established with the help of fuzzy and self tuning Adaptive fuzzy logic controller designed in Lab VIEW software. It combines the advantages of both fuzzy logic and self tuning Adaptive fuzzy logic controller. The implementation attempts to rectify the errors between the measured value and the set point which helps to achieve efficient temperature control. The Adaptive fuzzy controller uses defined rules to control the system based on the current values of input variables and temperature errors. The simulation results presented in order to evaluate the proposed method. The result shows that self tuning  Adaptive fuzzy logic controller was tolerant to disturbance and the temperature control is most accurate.

2018 ◽  
Vol 7 (2.24) ◽  
pp. 283 ◽  
Author(s):  
M Rathaiah ◽  
P Ram Kishore Kumar Reddy ◽  
P Sujatha

Renewable Energy Resources plays an active role in standing against   global warming and reduce the use of conventional energy sources. Hybrid systems formed by combining the renewable energy sources are efficient relatively. The intent of this paper is to furnish endurable power for frontier and far-off places with hybrid-system of architecture. The intended system embodying DFIG and solar PV based wind turbine. In solar systems, control mechanism is essential for improving the performance. This paper proposes a method of incremental conductance approach based MPPT Adaptive Fuzzy Logic Controller for grid connected PV system which is composed of a boost converter and a three phase inverter. Adaptive Fuzzy Logic Controller provides fast response and better %THD compared to Fuzzy and PI controllers. In solar system, MPPT will magnify solar output power value. The DFIG has two controllers Grid-Side Control (GSC) and Rotor-Side Control (RSC). The rated rotor speed and DC-link voltage are regulated by RSC and GSC through PI, Fuzzy Logic Controller and AFLC strategies. By using simulation studies performed by three control strategies, %THD analysis is carried out.  


2009 ◽  
Vol 36 (2) ◽  
pp. 1540-1548 ◽  
Author(s):  
Cetin Elmas ◽  
Omer Deperlioglu ◽  
Hasan Huseyin Sayan

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