Spatiotemporal chaotification of delta robot mixer for homogeneous graphene nanocomposite dispersing
Autor: | Ali Emre Kavur, Sibel Demiroglu Mustafov, Savas Sahin, Ozgur Seydibeyoglu, Cuneyt Guzelis, Özgün Başer, Yalcin Isler |
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Rok vydání: | 2020 |
Předmět: |
0209 industrial biotechnology
Nanocomposite Polymer nanocomposite Computer science General Mathematics Propeller Chaotic Feed forward 02 engineering and technology 7. Clean energy Sliding mode control Computer Science Applications 03 medical and health sciences Chaotic mixing 020901 industrial engineering & automation 0302 clinical medicine Control and Systems Engineering Control theory 030220 oncology & carcinogenesis Homogeneity (physics) Software Delta robot |
Zdroj: | Robotics and Autonomous Systems. 134:103633 |
ISSN: | 0921-8890 |
DOI: | 10.1016/j.robot.2020.103633 |
Popis: | This paper presents the design, implementation and polymer nanocomposite mixing application of a robust spatiotemporal chaotic delta robot. Blending fluids efficiently is a vital process for the preparation of graphene nanocomposite mixing. The most commonly used mixing materials are polymeric materials that need to be blended in non-Newtonian fluids. To achieve a superior blending performance over the conventional ones, it is used two different chaotification mechanisms for the realization of the spatiotemporal chaotic delta robot mixer system. One of them is for the chaotification of the mixer propeller while the second one is for the chaotification of the three-dimensional position of the endpoint of the delta robot. The model-based robust chaotification scheme based on sliding mode control is applied to chaotify the speed of the delta robot-mixer via dynamical state-feedback chaotification method. The chaotification of 3D position of the mixer is realized in a feedforward way by producing chaotic input signals. The implemented robust chaotic delta robot mixer exploits the efficacy of chaotic mixing in obtaining homogeneity in the mixture with less operation time, and hence reduced electrical energy consumption. In these performance evaluations, energy consumption and material characterization, which are measured by reliable material characterization methods such as X-ray diffraction, Fourier-transform-infrared spectroscopy, water contact angle, dynamical mechanical analysis, atomic force microscopy, Raman and field emission-scanning electron microscope analyses, are used as criteria. The obtained results show that, for the delta robot, the proposed chaotic-speed together with 3D chaotic-movement operation mode provides a better mixing performance than other mixing operation modes. (C) 2020 Elsevier B.V. All rights reserved. |
Databáze: | OpenAIRE |
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