Modeling of Cement-Bonded Sand Mould System

Author(s):  
B. Surekha ◽  
Pandu R. Vundavilli ◽  
M. B. Parappagoudar

The present paper deals with the forward mapping problem of cement bonded sand mould system using fuzzy logic (FL)-based approaches. It is important to note that the performance of an FL-based approach depends on its knowledge base (KB) that is, rule base and data base. Here, three approaches have been proposed to solve the said problem. The first Approach deals with the development of manually constructed Mamdani-based FL system, and the second Approach deals with the optimization of the rule base and data base of the FL system constructed in Approach 1, whereas the third Approach deals with automatic evolution of the FL system, in which the consequent part has also been optimized. A binary coded genetic algorithm (GA) has been used for the said purpose. The performances of the developed approaches are tested in forward mapping of a cement bonded sand mould system. It is to be noted that all the approaches can be effectively used to model the cement-bonded moulding sand system.

2013 ◽  
Vol 274 ◽  
pp. 345-349 ◽  
Author(s):  
Mei Lan Zhou ◽  
Deng Ke Lu ◽  
Wei Min Li ◽  
Hui Feng Xu

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%.


2016 ◽  
Vol 26 (1) ◽  
pp. 75-90 ◽  
Author(s):  
Dragan Pamucar ◽  
Darko Bozanic ◽  
Aleksandar Milic

The paper has focused on the point at which a decision is to be made to activate the Obstacle Employment Group (OEG), which is a defining moment for the overall engagement of the group. The course of action is selected based on a Fuzzy Logic System (FLS), created by translating the experience of decision-makers into a single knowledge base. The FLS mainstays are four input criteria and one output, interconnected by a rule base.


2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro

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.


2021 ◽  
Vol 1933 (1) ◽  
pp. 012069
Author(s):  
Yohanssen Pratama ◽  
Monalisa Pasaribu ◽  
Joni Nababan ◽  
Dayani Sihombing ◽  
Dicky Gultom

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