Stirring System Design for Automatic Coffee Maker Using OMRON PLC and PID Control

Setiawan, Ashadi; Ma’arif, Alfian

doi:10.31763/ijrcs.v1i3.457

Cited by 9 publications

(4 citation statements)

References 46 publications

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“…The PID control system is a type of feedback control system that utilizes a controller called Proportional-Integral-Derivative (PID) [82], [83], [84], [85], [86], [87], [88], [89]. This type of control system is commonly used in the basic design of motor control systems [90], [91], [92], [93], [94], [95].…”

Section: Pid Controller Designmentioning

confidence: 99%

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Chotikunnan

Pititheeraphab

2023

Journal of Robotics and Control

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This study aims to develop an expert system implementation of P controller and fuzzy logic controller to address issues related to improper control input estimation, which can arise from incorrect gain values or unsuitable rule-based designs. The research focuses on improving the control input adaptation by using an expert system to resolve the adjustment issues of the P controller and fuzzy logic controller. The methodology involves designing an expert system that captures error signals within the system and adjusts the gain to enhance the control input estimation from the main controller. In this study, the P controller and fuzzy logic controller were regulated, and the system was tested using step input signals with small values and larger than the saturation limit defined in the design. The PID controller used CHR tuning to least overshoot, determining the system's gain. The tests were conducted using different step input values and saturation limits, providing a comprehensive analysis of the controller's performance. The results demonstrated that the adaptive fuzzy logic controller performed well in terms of %OS and settling time values in system control, followed by the fuzzy logic controller, adaptive P controller, and P controller. The adaptive P controller showed similar control capabilities during input saturation, as long as it did not exceed 100% of the designed rule base. The study emphasizes the importance of incorporating expert systems into control input estimation in the main controller to enhance the system efficiency compared to the original system, and further improvements can be achieved if the main processing system already possesses adequate control ability. This research contributes to the development of more intelligent control systems by integrating expert systems with P controllers and fuzzy logic controllers, addressing the limitations of traditional control systems and improving their overall performance.

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Section: Pid Controller Designmentioning

confidence: 99%

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Chotikunnan

Pititheeraphab

2023

Journal of Robotics and Control

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“…1 and Fig. 2, two diagrams can be shown that represent each of the DC servo motor circuits, first, and the other represents a block for this motor [41][42][43][44][45]. From Fig.…”

Section: System Description and Mathematical Model Of DC Servomotormentioning

confidence: 99%

Design and Implementation of No Load, Constant and Variable Load for DC Servo Motor

Shneen,

Dakheel,

Abdullah

2023

Journal of Robotics and Control

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Simulations were conducted to improve and design an appropriate control system and obtain a model with the required development to suit the operation of the engine with constant and variable loads, which are the proposed working conditions that are suitable for many applications. The current simulation aims to build and design a model for an electric motor (DC Servo motor) and a model for a conventional controller (PID). The proposed model addresses the cases of fixed and variable loads in terms of using the controller that improves the performance of the motor’s work for different conditions. Three cases were developed to conduct the proposed tests, which included the case of no-load, fixed and variable load. Tests were conducted. Without the console and for the purpose of comparison and observation of improvement, the test was conducted with the addition of the console. The results showed system performance may improve depending on usage using traditional control systems. Performance measurement criteria are adopted for the purpose of comparison and observation of performance improvement. The criteria that are adopted are rise time and stability (steady state) in addition to the ratio of the rate of under and over-shoot. Where it can be deduced from this the possibility of using different control systems, including traditional ones, to improve performance, and they include controlling the speed of the motors, as well as controlling the effort, and the consequent effects on the subject of the study, as it deals with transient cases and changing operating conditions with more than acceptable efficiency and relatively high quality. There are four state simulation include, 1st at no load without controller: rise time equal 309.886ms , overshoot equal 44.203% and undershoot equal 9.597%.2nd at load without controller: rise time equal 216.319ms , overshoot equal 58.654% and undershoot equal 0.210%.3rd at no load with PID controller: rise time equal 1.177s , overshoot equal 0.505% and undershoot equal 1.914%.4th at load with PID controller: rise time equal 1.112s , overshoot equal 0.509% and undershoot equal 5.856%.

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“…Although traditional Proportional-Integral-Derivative (PID) control technology can achieve certain results in certain situations, it is hard to cater for the wants of contemporary industrial manufacturing for high precision and stability due to its difficult parameter adjustment and susceptibility to external interference (Tian et al, 2020). For example, Wang team and Setiawan team both proposed controllers based on PID control technology, but the PID controllers proposed all have the problem of unstable control effect (Wang and Lu, 2022;Setiawan and Ma'arif, 2021). Therefore, seeking a new control method to improve the effect of 8BSM is of great significance.…”

Section: Introductionmentioning

confidence: 99%

Dynamic modeling and optimization of an eight bar stamping mechanism based on RBF neural network PID control

Ma,

2024

Front. Mech. Eng.

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Introduction: Modern industrial manufacturing often requires the eight-bar stamping mechanism to have high motion accuracy and stability. To meet these stringent requirements, traditional control techniques such as proportional-integral-derivative (PID) control need to be improved.Methods: In this study, radial basis function neural network is introduced to improve the traditional proportional integral derivative control technique. The improved proportional integral derivative technique is applied to the modeling and optimization of eight kinds of bar stamping mechanisms.Results: Comparing the improved control technology, the experiment showed that the peak time and adjustment time of the improved technology were 0.516 s and 1.038 s, respectively, which are better than the comparative control technology. In addition, in the comparative analysis of the eight bar stamping mechanism, the proposed architecture scored 9.3 points in operational efficiency, which is significantly greater than the comparative architecture.Discussion: The results show that the combination of PID control strategy and radial basis function neural network provides a powerful tool for dynamic modeling and optimization of eight-bar stamping mechanism. It not only provides enhanced motion accuracy and stability, but also brings significant practicality to industrial manufacturing. This integration opens up new possibilities for improving the performance of complex mechanical systems to meet the evolving needs of modern manufacturing.

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Stirring System Design for Automatic Coffee Maker Using OMRON PLC and PID Control

Cited by 9 publications

References 46 publications

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Adaptive P Control and Adaptive Fuzzy Logic Controller with Expert System Implementation for Robotic Manipulator Application

Design and Implementation of No Load, Constant and Variable Load for DC Servo Motor

Dynamic modeling and optimization of an eight bar stamping mechanism based on RBF neural network PID control

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