Design of CAN-Bus Based Yarn Feeding Control System for Carpet Tufting Machine

Chen, Guang Feng; Zhai, Lin Lin; Zou, Kun; Yang, Yi; Wang, Wei Bin

doi:10.4028/scientific5/amr.459.275

Cited by 1 publication

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“…In 2012, Yan Ru [1] used single-chip microcomputer and wireless communication to achieve the goal of real time monitoring and automatic feeding to the drug machines. Guangfeng Chen proposed [2] a CANbus and stepper motor based yarn feeding control system for tufting carpet machine. In 2013, Lanjun Li [3] put forward a control system based on Advanced RISC Machines, touch panel and PLC to control the operation of feeding conveyer in automatic tomato selection assembly line.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Control Framework for the Feeding System in the Biomass Power Plant

Sun

Zhu

Cao

et al. 2015

MATEC Web of Conferences

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Abstract. This paper proposes an intelligent control framework for biomass drying process with flue gases based on FLC (fuzzy logic controller) and CAN (Controller Area Network) bus. In the operation of a biomass drying process, in order to get the biomass with the set-point low moisture content dried by waste high temperature flue gases, it is necessary to intelligent control for the biomass flow rate. Use of an experiment with varied materials at different initial moisture contents enables acquisition of the biomass flow rates as initial setting values. Set the error between actual straw moisture content and set-point, and rate of change of error as two inputs. the biomass flow rate can be acquired by the fuzzy logic computing as the output. Since the length of dryer is more than twenty meters, the integration by the CAN bus can ensure real-time reliable data acquisition and processing. The control framework for biomass drying process can be applied to a variety of biomass, such as, cotton stalk, corn stalk, rice straw, wheat straw, sugar cane. It has strong potential for practical applications because of its advantages on intelligent providing the set-point low moisture content of biomass feedstock for power generation equipment.

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Section: Introductionmentioning

confidence: 99%