Multi-Objective Optimization with Fuzzy Logic Analysis of Confined Flow Characteristics on Circular Cylinder

In this paper, an automatic procedure to perform the optimal sizing of a stand-alone solar electrical system with battery storage is developed by a fuzzy logic based multi-objective optimization approach. The procedure aims at finding the configuration that yields the best compromise for the two considered objectives: the long-term average performance and the overall cost of the generating system. In particular, the objectives of the optimization problem are: the maximization of the Supplied Load Fraction, that is the fraction of the actual electrical load that can be supplied by the system, and the minimization of the Relative Unit Electricity Cost, that is the net cost of generating each kWh during the lifetime of the stand-alone solar electrical system referred to the UEC calculated in case of loads supplied by the grid. The control variables are the solar cell array surface, the tilt angle of the modules, and the storage system capacity. The fuzzy multi-objective optimization procedure is described and the application results are presented considering different configurations characterized by some parameters, such as the electrical load, the yearly power demand, the distance from the utility grid, and the solar cells unit cost.

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Constrained multi-objective optimization of a fuzzy logic controller-applications in a non-linear system and a goal-seeking rover

Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003. ◽

10.1109/cca.2003.1223315 ◽

2004 ◽

Author(s):

H.S. Zadeh

Keyword(s):

Fuzzy Logic ◽

Linear System ◽

Fuzzy Logic Controller ◽

Multi Objective Optimization ◽

Multi Objective ◽

Non Linear ◽

Non Linear System

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Multi-Objective Optimization of Properties of Sponge Gourd-Bagasse Hybrid Reinforced Polymer Composite Using Fuzzy Logic, PSO, Modified Desirability Function and NSGA II

10.21203/rs.3.rs-678034/v1 ◽

2021 ◽

Author(s):

Ikechukwu Chibueze ◽

Chizoba Obele ◽

CHIDOZIE NWOBI-OKOYE ◽

Clement Atuanya

Keyword(s):

Mechanical Properties ◽

Fuzzy Logic ◽

Computational Models ◽

Desirability Function ◽

Fitness Function ◽

Golf Club ◽

Multi Objective Optimization ◽

Nsga Ii ◽

Multi Objective ◽

Sponge Gourd

Abstract Development of mathematical models for prediction of properties of materials is often complex and cumbersome. This led to the advent of simpler, and often more accurate, computational models based on artificial intelligence for predicting materials properties. The aim of this study is to predict the mechanical properties of a newly developed hybrid composite material made with sponge gourd, baggase and epoxy resin for golf club application using fuzzy logic (FL) and carry out a multi-objective optimization of the properties with modified desirability function (DF) and NSGA II algorithm. The inputs were %Wt of baggase, %Wt of Sponge gourd and Fiber size (µm) while the response variables were tensile strength, hardness, flexural strength, modulus, elongation and impact strength. The FL model was separately coupled, as fitness function, with the modified DF algorithm and the NSGA II algorithm respectively. The DF was optimized with particle swarm optimization (PSO) algorithm. The results showed that the FL model predicted the mechanical properties accurately and the minimum correlation coefficient (R) between the experimental responses and FL predictions was 0.9529. The modified algorithms took care of certain peculiarities in the desirability properties such as elongation whose desirability is constant over a range. The optimized properties were found to be worse if the optimization algorithms were not modified.

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