Temperature and water level control system in water thermal mixing process using adaptive fuzzy PID controller

Tunjung, D. M.; Prajitno, Prawito; Handoko, Djati

doi:10.1088/1742-6596/1816/1/012032

Cited by 9 publications

(3 citation statements)

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“…Water-cooled injection machines perform well in cooling speed, production e ciency, and qualities of plastic parts and are widely used in the manufacturing of plastic parts. e e ect of temperature control of injection machines is a key link in production quality and appearance [4][5][6]. Compared to traditional injection machines, water-cooled injection machines have more complex control systems.…”

Section: Introductionmentioning

confidence: 99%

Application of Expert Adjustable Fuzzy Control Algorithm in Temperature Control System of Injection Machines

2022

Computational Intelligence and Neuroscience

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The stability and accuracy of temperature control of the injection molding machine is one of the keys to determine the quality and appearance of plastic parts. Due to the temperature control system of water-cooled injection molding machine has the characteristics of coupling, nonlinearity, and hysteresis, the traditional proportion-integral-derivative (PID) method to control the barrel temperature of injection molding machine will yield temperature overshoot and oscillation, affecting the product and appearance quality. In order to improve the effect of barrel temperature control, in this paper, an expert adjustable fuzzy control strategy (EAFCA) is designed to optimize the barrel temperature control system through the combination of expert control, fuzzy control, and PID control. The expert control rules are designed according to the barrel temperature deviation e and its change rate ec. The expert rules are used to adjust the mapping range of the fuzzy universe in real time for the input and output variables of the fuzzy controller and finally to realize the accurate adjustment of the PID controller parameters. In terms of control systems, the distributed control system (DCS) monitoring system of injection molding machine is designed with Siemens CPU315-2PN/DP and industrial computer as the hardware core and Step7 and windows control center (WinCC) as the software platform to complete the tool plastic production monitoring system. The DCS improves the operability, data management convenience, and plastic production efficiency of the injection molding machine monitoring system. The Simulink simulation and field test show that the EAFCA method can increase the adjustment speed by approximately 34 s and reduce the overshoot by nearly 3.1%, which significantly improves the stability and accuracy of the barrel temperature and improves the quality of plastic parts.

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Section: Introductionmentioning

confidence: 99%

Application of Expert Adjustable Fuzzy Control Algorithm in Temperature Control System of Injection Machines

2022

Computational Intelligence and Neuroscience

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“…It does not need to establish a mathematical model. According to the input and output result data of the actual system and referring to the operating experience of field operators, the system can be controlled in real time [18]. Its fuzzy PID control flow chart is as shown in Figure 9 below, and its wheelchair rotation speed can be obtained by the encoder.…”

Section: Fuzzy Pid Control Of Tongue Control Systemmentioning

confidence: 99%

Non-Invasive Intraoral Stand-Alone Tongue Control System Based on RSIC-V Edge Computing

Shi,

Peng,

Zhao

et al. 2023

Applied Sciences

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The intelligent tongue control system is of great significance for assisting the independent life of patients with a limb disability. In order to more accurately control the assisted living equipment of incompetent patients and solve the power-loss problem of the intelligent tongue control system, this research designs a non-invasive pressure sensor array for tongue touch signal detection in the oral cavity and proposes a tongue control system based on RSIC-V edge computing. The system converts the tongue touch pressure data into specific control instructions on the edge of the RSIC-V chip and transmits them to the receiver, thus reducing the transmission of data. This study takes control of the wheelchair motor as the test object. In the experiment, the speed response time test, the center click task, and the power consumption experiment are carried out, whose results show that the adaptive fuzzy PID control algorithm has good robustness in the system; when the DC motor with a given speed of 750 r/min reaches the steady state, its rise time is 0.108 s and the adjustment time is 0.59 s. The dynamic power consumption of the non-intrusive intraoral stand-alone tongue control system proposed in this paper is found to be 3.745 MW, which is 11.5% lower than the total power consumption of the sTD system.

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“…At present, most manufacturers in our country realize temperature control with PID regulator.PID control algorithm has large time lag and inertia, so it is not suitable for the heat exchanger temperature control requirements of the thermal performance test bench [5][6][7] .With the development of intelligent control algorithm, fuzzy control and Smith estimation are gradually applied to the production process. Fuzzy control does not need to establish a mathematical model.The overshoot and steady-state error of the system response are small;Strong ability to restrain external interference and noise;With high stability, PID parameters can be optimized and adjusted according to different conditions .Smith predictive controller can effectively solve the problem of large time delay and inertia in temperature control.Therefore, this experiment designed a control algorithm combining traditional PID, fuzzy control and Smith's prediction [8][9][10] to improve the response speed, adjustment accuracy and anti-interference performance of the cold water outlet temperature control of the thermal performance test bench. '…”

Section: Introductionmentioning

confidence: 99%

Temperature control technology based on Smith fuzzy PID

Gu,

Zhu,

Guan

2024

Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023)

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In order to improve the response speed, adjustment accuracy and anti-interference performance of the outlet temperature of the heat exchanger of the thermal performance test bench. An algorithm combining fuzzy control, Smith prediction and traditional PID control is proposed, and use Matlab/Simulink to simulate the temperature characteristics and antiinterference characteristics of the system. The experimental results show that compared with the traditional PID and Fuzzy PID algorithms, the response speed of Smith fuzzy PID is 57S and 50S faster 8 than that of traditional PID and Smith PID, respectively, and the overshoot is 18% and 16% less than that of traditional PID and Fuzzy PID respectively.Combined with Smith prediction algorithm, the time lag problem is effectively solved. Therefore, the Smith fuzzy PID control method has a faster response to the outlet temperature control of the heat exchanger, a smaller overshoot, and a faster response to interference signals.

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Temperature and water level control system in water thermal mixing process using adaptive fuzzy PID controller

Cited by 9 publications

References 0 publications

Application of Expert Adjustable Fuzzy Control Algorithm in Temperature Control System of Injection Machines

Application of Expert Adjustable Fuzzy Control Algorithm in Temperature Control System of Injection Machines

Non-Invasive Intraoral Stand-Alone Tongue Control System Based on RSIC-V Edge Computing

Temperature control technology based on Smith fuzzy PID

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