Algorithm for reasoning with words based on linguistic fuzzy cognitive map

Hán, Nguyễn Văn; Hao, Nguyen Cong

doi:10.1002/cpe.6415

“…The processing of the fuzzy PID controller is shown in Figure 4, It consists of three steps: fuzzification [25], fuzzy inference, and defuzzification. The inputs to the fuzzy design of the extruder temperature control system in this paper are the temperature setpoint and the sensor detection of the actual temperature error e and the rate of change of the error ec [26]. The output is: ∆Kp、∆Ki、 ∆Kd.First, the theoretical do-mains of e and ec are transformed into fuzzy domains by quantization factors Ke, Kec,setting the fuzzy domains of e, ec and ∆Kp to [-6, 6] and the domains of ∆Ki, ∆Kd to [0,6].…”

Section: Variable Universe Fuzzy Pid Controller Designmentioning

confidence: 99%

Research and application of adaptive anti-interference based VU-fuzzy-PID algorithm in temperature control system of platic extruder

Meng,

Sun,

Ruan

et al. 2024

Preprint

0

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Plastic profiles, as the basic material for social and economic development, are mainly processed and moulded by plastic extruders. In the production process of plastic profiles, the temperature precision control of plastic extruder directly affects the plasticising and mixing effect of raw mate-rials. Therefore, the development of high-precision, fast response and stable plastic extruder tem-perature control system plays a key role in the development of plastic profile industry. In order to solve the shortcomings of the plastic extruder such as low temperature precision, slow response speed and poor anti-interference ability, the author has established a plastic extruder temperature control system model based on the study of PID control strategies and fuzzy PID control strategies, combined with the structural and functional characteristics of plastic extruder. Adopting a variable universe fuzzy PID control strategy to improve the performance of the plastic extruder temperature control system. The core idea of this strategy is to introduce proportional factors to change the range of the fuzzy domain. Under the condition that the fuzzy rules remain unchanged, the fuzzy domain compresses as the error decreases and expands as the error increases. Changing the domain is equivalent to adding fuzzy control rules within the same domain, thereby completing the dynamic adjustment of PID controller parameters. Through MATLAB simulation analysis and comparison, it was found that this control strategy has the advantages of short rise time, no overshoot, and strong anti-interference compared to PID control and fuzzy PID control strategies. Finally, through ex-perimental verification, it was found that this control strategy significantly changes the temperature control effect of nonlinear time-varying extruders, and has good adaptability and stability.

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“…The processing of the fuzzy PID controller is shown in Figure 4, It consists of three steps: fuzzification [25], fuzzy inference, and defuzzification. The inputs to the fuzzy design of the extruder temperature control system in this paper are the temperature setpoint and the sensor detection of the actual temperature error e and the rate of change of the error ec [26]. The output is: ∆Kp、∆Ki、 ∆Kd.First, the theoretical domains of e and ec are transformed into fuzzy domains by quantization factors Ke, Kec,setting the fuzzy domains of e, ec and ∆Kp to [-6, 6] and the domains of ∆Ki, ∆Kd to [0,6].…”

Section: Variable Universe Fuzzy Pid Controller Designmentioning

confidence: 99%

Research and Application of Plastic Extruder Temperature System Based on Variable Universe Fuzzy PID Control

Meng

¹

,

Gao

²

,

Ruan

³

et al. 2023

Preprint

0

View full text Add to dashboard Cite

Plastic profiles, as the basic material for social and economic development, are mainly processed and moulded by plastic extruders. In the production process of plastic profiles, the temperature precision control of plastic extruder directly affects the plasticising and mixing effect of raw mate-rials. Therefore, the development of high-precision, fast response and stable plastic extruder tem-perature control system plays a key role in the development of plastic profile industry. In order to solve the shortcomings of the plastic extruder such as low temperature precision, slow response speed and poor anti-interference ability, the author has established a plastic extruder temperature control system model based on the study of PID control strategies and fuzzy PID control strategies, combined with the structural and functional characteristics of plastic extruder. Adopting a variable universe fuzzy PID control strategy to improve the performance of the plastic extruder temperature control system. The core idea of this strategy is to introduce proportional factors to change the range of the fuzzy domain. Under the condition that the fuzzy rules remain unchanged, the fuzzy domain compresses as the error decreases and expands as the error increases. Changing the domain is equivalent to adding fuzzy control rules within the same domain, thereby completing the dynamic adjustment of PID controller parameters. Through MATLAB simulation analysis and comparison, it was found that this control strategy has the advantages of short rise time, no overshoot, and strong anti-interference compared to PID control and fuzzy PID control strategies. Finally, through ex-perimental verification, it was found that this control strategy significantly changes the temperature control effect of nonlinear time-varying extruders, and has good adaptability and stability.

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