Design and implementation of fuzzy logic controller for level control

Lamkhade, Poonam N.; Parvat, B.J.; Kadu, C.B.

doi:10.1109/icesa.2015.7503395

Cited by 11 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The central idea of using metaheuristics in the pursuit of optimizing FLC performance is in the design characteristic of this controller. The various parameters and variables that are necessary for the good functioning of the FLC do not present general rules, making the role of the operator essential in the analysis and dimensioning of these terms [11].…”

Section: Flc Optimizationmentioning

confidence: 99%

See 1 more Smart Citation

Fuzzy Logic Control with PSO Tuning

Silva¹

2022

Fuzzy Systems - Theory and Applications

View full text Add to dashboard Cite

Several applications of artificial intelligence in the area of control of dynamic systems have proven to be an efficient tool for process improvement. In this context, control systems based on fuzzy logic - Fuzzy Logic Control (FLC) are part of a series of advances in the areas of control systems. Fuzzy control is based on natural language and therefore has the ability to make approximations closer to the real nature of the problems. The use of metaheuristic algorithms such as the particle swarm optimization (PSO) allows it to provide adequate adjustments to the fuzzy controller in an optimized manner. This technique allows to adjust the FLC in a simple way according to the performance desired by the designer, without the need for a long time of conventional tests.

show abstract

Section: Flc Optimizationmentioning

confidence: 99%

“…Despite the specialist's knowledge, the resulting FLC may not perform as optimally. Metaheuristics, on the other hand, can function as an intelligent search engine for the various possible architectures for the FLC, without the need for the exhaustive work of trial and error on the part of an expert control engineer [11][12][13].…”

Section: Flc Optimizationmentioning

confidence: 99%

Fuzzy Logic Control with PSO Tuning

Silva¹

2022

Fuzzy Systems - Theory and Applications

View full text Add to dashboard Cite

show abstract

“…A base de regras fuzzy consiste em um conjunto de regras para controlar o sistema. Já o mecanismo de inferência avalia quais regras de controle são relevantes no momento atual e decide qual deve ser a entrada para a planta (Lamkhade et al, 2015).…”

Section: Figura 3 Arquitetura Do Controlador Fuzzyunclassified

“…O conhecimento e a experiência do especialista são convertidos em um nível de máquina facilmente com a ajuda de regras e, em seguida, colocados em uma base de regras do controlador para tomar as decisões adequadas. Portanto, a implementação do controlador torna-se fácil e pode ser obtida sem modelagem matemática complexa (Lamkhade et al, 2015). Trabalhos como o de Bhandare and Kulkarni (2015) ressaltam que o controlador Fuzzyé usado para obter uma boa resposta em sistemas reais de natureza nãolineares, respostas essas que controladores convencionais nem sempre são capazes de fornecer.…”

Section: Introductionunclassified

Projeto de um Controlador Fuzzy Aplicado em um Tanque de Nível de uma Planta didática de Processos Industriais

Oliveira

Junior

Martins

et al. 2019

Anais Do 14º Simpósio Brasileiro De Automação Inteligente

View full text Add to dashboard Cite

In this work a study and the implementation of level control is presented, using the MPS-PA Festo industrial process module. This process has non-linear characteristics, and it was initially analysed in closed-loop, where, after watching its response, it was developed via MATLAB a fuzzy controller. To test the performance of the fuzzy controller, it was compared with a PI controller. The experimental results show a basis for comparation between the two control techniques. Resumo: Neste trabalhoé apresentado um estudo e implementação do controle de nível no modulo didático de processos industriais MPS-PA Festo. Este processo, que apresenta características não lineares foi analisado inicialmente em malha fechada, no qual, após um estudo das características de sua resposta, implementou-se, via MATLAB um controlador fuzzy. Para avaliar o desempenho do controlador fuzzy, será realizada uma comparação com o controlador PI. Os resultados obtidos experimentalmente apresentam uma base para a comparação entre as duas técnicas de controle.

show abstract

“…Fuzzy control [1]- [3] is an advanced control methodology that was first introduced by Professor Lotfi at the University of California, Berkeley, in 1965 [4]. This methodology has since undergone continuous development and has achieved milestones, making it a widely used algorithm in the field of control systems.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Controller from Experts’ Rules for Middle Axis Ball and Beam

Nguyen,

Trinh

et al. 2023

JFSC

View full text Add to dashboard Cite

The present study examined the nonlinear system of Ball and Beam, to design an intelligent controller for this dynamic system. The authors formulated a mathematical model for the system and performed simulation testing using MATLAB to control it. It is noteworthy that the mathematical model was exclusively used for simulation purposes and not for building the controller. The author's team then proceeded to develop a Fuzzy Controller for the simulation model of the Ball and Beam system. Subsequently, the team tested the Fuzzy controller on the actual Ball and Beam model. The primary objective of this study was to assess the feasibility of building and controlling an intelligent controller for a nonlinear object, without relying on its mathematical model. The findings of the study can be useful in designing and controlling complex systems that are difficult to model mathematically.

show abstract

Design and implementation of fuzzy logic controller for level control

Cited by 11 publications

References 10 publications

Fuzzy Logic Control with PSO Tuning

Fuzzy Logic Control with PSO Tuning

Projeto de um Controlador Fuzzy Aplicado em um Tanque de Nível de uma Planta didática de Processos Industriais

Fuzzy Controller from Experts’ Rules for Middle Axis Ball and Beam

Contact Info

Product

Resources

About