scholarly journals Microtension control for a yarn winding system with an IMC PID controller

2019 ◽  
Vol 20 (6) ◽  
pp. 609 ◽  
Author(s):  
Qing Wang ◽  
Anqing Li ◽  
Yuanyuan Li ◽  
Jixin Liu ◽  
Hui Shen ◽  
...  

In this paper, feedforward compensation and an internal model control (IMC) PID tuning method to maintain the yarn tension within a micro-boundary range are proposed. The proposed method can be used to improve the quality of products in textile industry. We first develop a mathematical model of the AC servo motor and yarn tension system. Based on the results of the mathematical model, an IMC PID controller is designed to control the microtension of the yarn. The proposed IMC-PID controller can be directly calculated from the time constant and time delay. Feedforward control is used to compensate for the linear velocity of the winding roller. To reduce the lateral vibrations of the yarn, we designed an active roller to nip the moving yarn. The active roller compensates for the variation in the diameter of the unwinding roller. The proposed method effectively improves the dynamics performance and the robustness of the system, and is appropriate for industrial application. Experimental instruments, including a tension sensor, an AC servo motor and a motion controller, equipped with a computer, are used to test the proposed method. The simulation and experimental results show the effectiveness of the proposed controller for the yarn microtension control system.

2020 ◽  
Vol 19 (1) ◽  
pp. 33-40
Author(s):  
Abdul Wali Abdul Ali ◽  
Abdullah Hadi Alquhali

This paper focuses on the simulation analysis of the conventional Internal Model Control (IMC) technique and the development of two proposed control techniques for the position control of AC Servo Motor. Internal Model Control (IMC) technique [1] was only able to control the AC Servo Motor under static load condition. Also, it had step response problems, and it was not robust against external disturbances. For these reasons, the IMC technique was further improved to control the AC Servo Motor under dynamic load conditions by proposing Amended Internal Model Controller (AIMC). The step response and the robustness of AIMC against external disturbances were further improved by proposing AIMC+FLC. Where a Fuzzy Logic Controller (FLC) is designed and connected with the AIMC.


Author(s):  
Noppanan Suwanjatuporn ◽  
Mes Napaamporn ◽  
Waree Kongprawechnon ◽  
Sirisak Wongsura

2018 ◽  
Vol 22 (S1) ◽  
pp. 2273-2283
Author(s):  
Haoliang Lv ◽  
Xiaojun Zhou

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
Jie Duan ◽  
Mingfeng Li ◽  
Teik C. Lim ◽  
Ming-Ran Lee ◽  
Ming-Te Cheng ◽  
...  

Conventional active control of road noise inside a vehicle cabin generally uses a pure feedforward control system with the conventional filtered-x least mean square (FXLMS) algorithm. While it can yield satisfactory noise reduction when the reference signal is well correlated with the targeted noise, in practice, it is not always possible to obtain a reference signal that is highly coherent with a broadband response typically seen in road noise. To address this problem, an active noise control (ANC) system with a combined feedforward–feedback controller is proposed to improve the performance of attenuating road noise. To take full advantage of the feedforward control, a subband (SFXLMS) algorithm, which can achieve more noise attenuation over a broad frequency range, is used to replace the conventional FXLMS algorithm. Meanwhile, a feedback controller, based on internal model control (IMC) architecture, is introduced to reduce the road noise components that have strong response but are poorly correlated with the reference signals. The proposed combined feedforward–feedback ANC system has been demonstrated by a simulation model with six reference accelerometers, two control loudspeakers and one error microphone, using actual data measured from a test vehicle. Results show that the performance of the proposed combined controller is significantly better than using either a feedforward controller only or a feedback controller only, and is able to achieve about 4 dBA of overall sound pressure level reduction.


Author(s):  
Xiaohong Wang ◽  
Likai Zheng ◽  
Thi Thu Giang Hoang ◽  
Zhifeng Pan ◽  
Xiaozhuang Zhou

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