scholarly journals An Optimization Scheme Based on Fuzzy Logic Control for Efficient Energy Consumption in Hydroponics Environment

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 289 ◽  
Author(s):  
Azimbek Khudoyberdiev ◽  
Shabir Ahmad ◽  
Israr Ullah ◽  
DoHyeun Kim
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Objective Function ◽  
Fuzzy Logic Control ◽  
World Population ◽  
Optimization Scheme ◽  
Efficient Energy ◽  
Logic Control ◽  
The World ◽  
The Cost

As the world population is increasing rapidly, food and water demands are the most crucial problem for humanity. In some areas of the world, water or environment is unsuitable for plant growth; hydroponic systems can provide a suitable environment for crop production with effective management of natural resources. Internet of Things paradigm based automated systems has been creating an excellent opportunity for monitoring and controlling agriculture by minimizing the cost and maximizing the profit significantly over the past decade. The reduction of the cost can be achieved by sufficient usage of resources and setting up optimum operational parameters for agricultural devices. This paper presents an optimization scheme with novel objective function for hydroponics environment parameters management with efficient energy consumption. The proposed approach provides optimal energy and resource utilization in the hydroponics system with setting up a working level and operational duration to the actuators. We have developed an optimization scheme with objective function for optimal humidity and water level control based on fuzzy logic, which can support the optimal measurement for crop growth with energy efficiency. Fuzzy logic control is applied for the compromise between actuators working level and operational duration. A real hydroponics environment has been implemented and presented to evaluate the effectiveness of the proposed approach. It can be assessed through the simulation results that the optimization module achieves a signification reduction (18%) in energy consumption as compared to the other scheme.

Modeling of Electric Vehicle Air Conditioning System and Analysis of Energy Consumption

2012 ◽  
Vol 516-517 ◽  
pp. 1164-1170 ◽  
Author(s):  
Jin Rui Nan ◽  
Yao Wang ◽  
Zhi Chai ◽  
Jun Kui Huang
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Electric Vehicle ◽  
Fuzzy Logic Control ◽  
Air Conditioning ◽  
Control Method ◽  
Air Conditioning System ◽  
Logic Control ◽  
Ac Motor ◽  
Total Vehicle

An simulation model for pure electric vehicle air conditioning system is established in MATLAB/ Simulink environment. The critical component of air conditioning system is selected and simulated. Fuzzy logic control method is used in AC motor controlling strategy. Combined with ADVISOR, the total vehicle energy consumption and AC energy consumption are simulated and calculated. The research indicate that by using Fuzzy logic control led AC system, the vehicle’s economcial effeciency improved. Life mileage is longer than the EV with traditional AC system and a better effect of energy saving is achieved.

scholarly journals Energy-demographic history of the modern civilization

POPULATION ◽  
2021 ◽  
Vol 24 (2) ◽  
pp. 142-153
Author(s):  
Vladimir Tetelmin
Keyword(s):  
Energy Consumption ◽  
Energy Production ◽  
Demographic History ◽  
World Population ◽  
Continuous Increase ◽  
Safe Level ◽  
World Energy ◽  
The World ◽  
History Of ◽  
The Cost

The continuous increase in human energy production per caput is accompanied by an increase in the world population. The work considers the demographic history of civilization as a function of the growing production and use of the energy by mankind. The evolution in the «energy-man» system took place relatively safely for the biosphere and a man up to the value of the per caput energy consumption of 11,000 kW*h/year*person that was achieved by civilization in 1950. Modern high per caput energy consumption of civilization is achieved at the cost of the loss of the environment-forming functioning by the biosphere and at the cost of the loss of the psychophysical health of a person. We can see the prospects for development of civilization through analysis of the energy-demographic history of mankind over the past 200 years. The features of fertility and mortality in the world are considered depending on the per caput energy consumption with a forecast for the future. Two limits to the growth of global energy production were formulated in terms of preventing harm to humans. Corresponding analytical dependencies are proposed. To prevent an ecological and demographic catastrophe and ensure transition of civilization to sustainable development, it is proposed to reduce the world energy production to 140*1012 kW*h/year with a decrease in per caput energy consumption to a relatively safe level of 18,000 kW*h/year*person, which existed in society in 1970. After this «step back» civilization will enter a state of relatively safe existence.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

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

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.

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