Design of Synthetic Optimizing Neuro Fuzzy Temperature Controller for Twin Screw Profile Plastic Extruder Using Labview

Ravi, S.; Balakrishnan, P.; Marimuthu, C. N.; Sujitha, C.

doi:10.1080/10798587.2013.771453

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…Figure shows the diagram for the PID control action, with e being the error signal entering the controller, u the control signal leaving the controller, r the value desired, and s the value measured in the output of the process. Equation shows the transfer function for the PID control action .

G_{P I D} (S) = K_{P} + \frac{K_{p}}{T_{i} S} + K_{p} T_{d} S

…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Design of an analysis virtual tool for PV sourced microgrid systems

Nolasco¹,

Padilla-Medina²,

Gutiérrez

et al. 2018

Comp Applic In Engineering

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This work presents the development of a virtual tool used in the power management of a microgrid connected to a PV arrangement. The virtual tool proposes five different control strategies used as main power management controller. Those strategies can be selected and compared to evaluate their different time responses and overall characteristics. In addition, results of an integrative evaluation of the virtual tool is reported, which was conducted using different Learning Gain Surveys. It was found that this pedagogical approach was appreciated by students and they learned the main concepts in spite of this methodology was new for them. Final recommendation and conclusions are provided at the end of this paper.

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G_{P I D} (S) = K_{P} + \frac{K_{p}}{T_{i} S} + K_{p} T_{d} S

…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Design of an analysis virtual tool for PV sourced microgrid systems

Nolasco¹,

Padilla-Medina²,

Gutiérrez

et al. 2018

Comp Applic In Engineering

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“…. A self-developed temperature control subsystem based on LabVIEW ® is employed to generate the high-temperature environment [15,16]. e hardware connection is shown in the bottom half of Figure 4.…”

Section: Experimental Veri Cation Of Ermal Environment Simulation Systemmentioning

confidence: 99%

Experimental Investigation of Thermal Modal Characteristics for a Ship’s Foundation under 300°C

Ding

Bai

et al. 2019

Shock and Vibration

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How to further reduce vibration and noise is a major challenge for modern ship design. High-temperature environment will significantly influence the mechanical properties (such as elastic modulus and stiffness) of the ship’s foundation. These properties will have a serious impact on the inherent vibration characteristics of the foundation. In this paper, a simplified foundation is taken as the research object, and a thermal-vibration joint test system is developed for investigating the thermal modal characteristics of the foundation under different temperatures. The joint test system consists of a transient aerodynamic heating environment simulation system and a vibration excitation and acquisition system. Finite element method (FEM) is used to analyze the distribution of thermal fields. The influence of the ceramic rods and the different ambient temperatures on the modal characteristics of the foundation is studied. The results indicate that the effect of ceramic rods on the modal characteristic of the foundation is negligible. The results also show that the greater the vibration response amplitude is as the temperature increases and the first-order natural frequency does not change, the smaller the second-order natural frequency and the damping ratio will become smaller. The variation of natural frequency and damping ratio of the foundation under different temperature conditions can provide a reliable experimental basis for the design of the vibration and noise reduction of the ship’s foundation in the thermal-vibration environment.

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“…The results showed that a FLC can perform well with a lesser overshoot than a PI controller. Another work carried out by them [38,39] found that a neurofuzzy controller gave better performance than fuzzy logic and PID controllers in extruder barrel temperature control. In fact, all of these studies based on AI techniques have focused only on the control of the barrel set temperatures in their set limits and did not attempt to control the melt temperature.…”

Section: B Control Schemes Based On Artificial Intelligence Techniquesmentioning

confidence: 99%

Single screw extrusion control: A comprehensive review and directions for improvements

Abeykoon

2016

Control Engineering Practice

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Polymer extrusion is usually a complex process, particularly due to the coupled nature of process parameters, and hence highly prone to fluctuations. Although a number of different approaches have been attempted in research/industry over the last few decades for extrusion control, it is still experiencing some problems in achieving consistent product quality. Presently, most of the polymer processing extruders are equipped with PID controllers mainly for the control of the screw speed and barrel temperatures in their set limits. It seems that only both of these controllers are commonly used as the major aids of process control to achieve the required melt quality. Although, the quality of the melt output (i.e., a thermally homogeneous melt output which is constant in quantity and quality over the time) is the key variable in polymer extrusion, only a few control techniques are available which make control decisions by observing the actual melt flow quality. Therefore, the development of new control strategies which consider the actual melt quality, perhaps incorporating industrially popular nonlinear techniques such as artificial intelligence, should be highly valuable. In this work, a critical evaluation is made on the state-of-the-art of the previous control approaches in polymer extrusion in industry and research while identifying their limitations. Then, some of the possible directions for future research and also to develop an advanced process control strategy are presented by eliminating a few of the existing limitations.

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Design of Synthetic Optimizing Neuro Fuzzy Temperature Controller for Twin Screw Profile Plastic Extruder Using Labview

Cited by 6 publications

References 7 publications

Design of an analysis virtual tool for PV sourced microgrid systems

Design of an analysis virtual tool for PV sourced microgrid systems

Experimental Investigation of Thermal Modal Characteristics for a Ship’s Foundation under 300°C

Single screw extrusion control: A comprehensive review and directions for improvements

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