Design, implementation, and simulation of a PLC based speed controller using fuzzy logic

Graham, Alexander; Etezadi-Amoli, M.

doi:10.1109/pess.2000.867380

Cited by 11 publications

(4 citation statements)

References 6 publications

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“…Fuzzy systems are relatively easy of using in practice and the mathematical knowledge is not complex. However, to program them a software engineer needs deep understanding of the industrial process inaccuracy and uncertainty [13][14][15][16].…”

Section: Automation Systemmentioning

confidence: 99%

Automation System Applied To A Plasma Inertization Plant

Guimarães¹,

Medeiros²,

Sousa³

et al. 2007

Eletrônica de Potência

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This article describes an automation system for a residues treatment plant based on thermal plasma. A compact PLC was used to activate several subsystems and to control the main reactor inner temperature using Fuzzy logic. A human-machine interface allows the monitoring of the variables and the activations of devices of the system remotely. An OPC communication is used to link the computer and the PLC.

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Section: Automation Systemmentioning

confidence: 99%

Automation System Applied To A Plasma Inertization Plant

Guimarães¹,

Medeiros²,

Sousa³

et al. 2007

Eletrônica de Potência

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“…The real life experiments of fuzzy logic traction/braking control have mainly been carried out in automobile platform or in-lab environment [17][18][19]. A number of researches have been performed on fuzzy logic aiming for improvement of motor traction control performance based on industrial programmable logic controller (PLC) [20][21][22][23] and other hardware platforms [24]. All these methods claim the effectiveness of their proposed creep/traction controller; however, these conclusions were not validated on a comprehensive locomotive dynamic model.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic creep control for a 2D locomotive dynamic model under transient wheel-rail contact conditions

Tian¹,

Daniel²,

Liu³

et al. 2014

WIT Transactions on the Built Environment

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In recent decades, advanced power-electronics-based control techniques have been widely used to electric drives for the traction of modern locomotives. However, the dynamic response of such locomotives under transient conditions due to external perturbations has not been fully investigated. In this work, an integrated dynamic model for a typical Co-Co locomotive/track system is developed to provide predictive simulations of the motion and forces transmitted throughout the whole locomotive dynamic system. The model integrates a 2D longitudinal-vertical locomotive structural vibration model, wheel/rail contact mechanics using Polach's creep force model, a simplified dynamic traction model and a fuzzy logic creep controller to simulate the transient response to a change in friction conditions. It is found that the proposed fuzzy logic controller has the advantage over a PI controller in terms of achieving higher tractive force under transient contact conditions.

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“…The use of fuzzy strategies as an expert system applied to PID constant regulation is an approach that must be considered when a PLC with a close loop system is going to be implemented to control complex and nonlinear plants [22]. In the same way, some works present different perspectives on Fuzzy Logic Control (FLC) applied to induction motors based on PLC built-in implementation [23][24][25] or remotely via a PC and a network [26].…”

mentioning

confidence: 99%

An Intelligent Controller Based on LAMDA for Speed Control of a Three-Phase Inductor Motor

Morales,

Fabara,

Pozo

2023

Emerg Sci J

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Three-phase induction motors are widely used in the industrial field due to their low cost and robustness; therefore, it is essential to continuously develop new proposals that improve their behavior and response in applications where speed control is required. This paper proposes the development of an intelligent controller programmed in a PLC and interconnected with a three-phase induction motor through a VFD. The novel intelligent controller bases its operation on the LAMDA algorithm, which acts as a decision-making system based on the state of the error with respect to the speed reference and its derivative, obtaining a closed-loop controller. In addition, the VFD receives commands from the PLC to operate the motor at a constant voltage-frequency ratio in which flux remains constant. The proposed controller has been validated in two study cases: i) reference changes and ii) rejection of disturbances. The results obtained are promising and show a good performance of the LAMDA controller when compared qualitatively and quantitatively with the controller most commonly used in industrial systems, such as PID, and controllers with similar characteristics, such as fuzzy, based on Mamdani and Takagi-Sugeno inference. Doi: 10.28991/ESJ-2023-07-03-01 Full Text: PDF

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Design, implementation, and simulation of a PLC based speed controller using fuzzy logic

Cited by 11 publications

References 6 publications

Automation System Applied To A Plasma Inertization Plant

Automation System Applied To A Plasma Inertization Plant

Fuzzy logic creep control for a 2D locomotive dynamic model under transient wheel-rail contact conditions

An Intelligent Controller Based on LAMDA for Speed Control of a Three-Phase Inductor Motor

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