scholarly journals A Data-driven Improved Fuzzy Logic Control Optimization-simulation Tool for Reducing Flooding Volume at Downstream Urban Drainage Systems

2020 ◽  
Author(s):  
Jiada Li
Author(s):  
YH Yau ◽  
CP Chang

The current research presents the study of the proposed thermostat setting developed in the previous work through a numerical simulation project using transient system simulation tool. The transient system simulation tool code is used to integrate the fuzzy logic to optimise a room thermostat with the multi-zone building model (Type56a). A set of equations is designed in the transient system simulation tool project to represent the fuzzy logic control system of the proposed thermostat setting. The performance analysis for the air-conditioning system installed with and without the application of the control system in terms of the operative zone temperature, the sensible cooling demand, the solar radiation, and the internal gains for a thermal zone for recent years or 2000s, and for the years 2020, 2050 and 2080 were comprehensively examined. Estimations of both predicted mean vote and predicted percentage of dissatisfied persons of the zone were also investigated. The findings indicate that a considerable amount of sensible cooling demand of approximately 8420 kJ/h or equivalent to 3.54% can be saved with the application of the proposed thermostat setting. The predicted mean vote is in the range from −0.22 to 0.72 with its average between 0.20 and 0.26 for the AC system installed with fuzzy logic control. These results further suggest that the thermal comfort of occupants can be improved taking into account their activity level, clothing insulation, indoor air temperature, air velocity, mean radiant temperature and relative humidity.


Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory


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.


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