GA optimisation of rule base in a fuzzy logic control of a solar power plant

2002 ◽  
Author(s):  
P.C.K. Luk ◽  
L.L. Lai ◽  
T.L. Tong
Keyword(s):  
Fuzzy Logic ◽  
Power Plant ◽  
Fuzzy Logic Control ◽  
Solar Power ◽  
Rule Base ◽  
Solar Power Plant ◽  
Logic Control

Fuzzy logic control of a solar power plant

1995 ◽  
Vol 3 (4) ◽  
pp. 459-468 ◽  
Author(s):  
F.R. Rubio ◽  
M. Berenguel ◽  
E.F. Camacho
Keyword(s):  
Fuzzy Logic ◽  
Power Plant ◽  
Fuzzy Logic Control ◽  
Solar Power ◽  
Solar Power Plant ◽  
Logic Control

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

FUZZY LOGIC CONTROL APPLICATION IN A NUCLEAR POWER PLANT

2002 ◽  
Vol 35 (1) ◽  
pp. 239-244
Author(s):  
Zhengyu Huang ◽  
Kwang Y. Lee ◽  
Robert M. Edwards
Keyword(s):  
Fuzzy Logic ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Fuzzy Logic Control ◽  
Nuclear Power ◽  
Logic Control ◽  
Control Application

Optimized Fuzzy Logic Control Strategy for Parallel Hybrid Electric Vehicle Based on Genetic Algorithm

2013 ◽  
Vol 274 ◽  
pp. 345-349 ◽  
Author(s):  
Mei Lan Zhou ◽  
Deng Ke Lu ◽  
Wei Min Li ◽  
Hui Feng Xu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Membership Functions ◽  
Logic Control

For PHEV energy management, in this paper the author proposed an EMS is that based on the optimization of fuzzy logic control strategy. Because the membership functions of FLC and fuzzy rule base were obtained by the experience of experts or by designers through the experiment analysis, they could not make the FLC get the optimization results. Therefore, the author used genetic algorithm to optimize the membership functions of the FLC to further improve the vehicle performance. Finally, simulated and analyzed by using the electric vehicle software ADVISOR, the results indicated that the proposed strategy could easily control the engine and motor, ensured the balance between battery charge and discharge and as compared with electric assist control strategy, fuel consumption and exhaust emissions have also been reduced to less than 43.84%.

Sign in / Sign up

Export Citation Format

Share Document