Fuzzy pid control of electromechanical actuator system

Li, Cuicui; Yi, Wei-Jian; Yin, Hongqiao; Guan, Jiancheng

doi:10.1088/1742-6596/1721/1/012052

Cited by 9 publications

(3 citation statements)

References 9 publications

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“…It uses each neuron in the artificial intelligence neural network to simulate different nodes of the power system. By connecting these neurons, a complete power system neural network is constructed, which automatically captures and analyzes the data and images generated by each circuit in operation, helping the power automation system to optimize the transmission scheme, reduce power loss and improve power supply capacity [1][2].…”

Section: Introductionmentioning

confidence: 99%

Application of neural network algorithm in electromechanical automatic control system

2023

Second International Conference on Electronic Information Technology (EIT 2023)

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In order to understand the application effect of electromechanical automatic control system, a neural network algorithm in the application of electromechanical automatic control system is proposed. This paper firstly analyzes the concept of electrical automation and neural network algorithm in detail, and then describes the advantages of neural network algorithm in electrical automatic control. Finally, the application of neural network algorithm in electrical automatic control is analyzed. In this paper, the application of neural network algorithm in electrical engineering automation is analyzed, and some suggestions are provided for the development of electrical engineering automation.

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Section: Introductionmentioning

confidence: 99%

Application of neural network algorithm in electromechanical automatic control system

2023

Second International Conference on Electronic Information Technology (EIT 2023)

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“…In [13] the The researchers presented one of the control methods, which is a control unit by adopting fuzzy logic to organize and tune the traditional type of Fuzzy-PI to obtain better performance of electric motor I.M, where the FLC controller adjusts within various work tests that include an operating condition without load, as well as the variable and constant load conditions, according to the reliability of the parameters of the conventional controller and its design according to the best results compared to the performance measures used to determine the parameters of the conventional PI controller. The traditional PID controller widely used in the electromechanical actuator control systems in process industries because of its accurate, high reliability, simple design and efficient turning of parameters (ki, kp, kd) [14][15][16][17][18]. The pid controller has the ability to have a good output response to a rotational speed for DC motor, but the parameter tuning implementation of this controller is complicated The PID controller has the ability to get a good output response represented by the rotational speed of the DC servo electric motor, but to implement and adjust the parameters of the conventional controller may be somewhat complicated [19][20].…”

Section: Introductionmentioning

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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“…This is actually how it works, P will determine the reaction to the current error which can lead to improvement of rise time while I, determine the reaction of the summation towards the recently appeared error which can reduce the steady-state error and as for D, determine the reaction following the rate of error changing which means D can predict the future error based on the rate of the current changed which can reduce the overshoot [21]- [23]. PID can be used on its own or even hybrid with another algorithm such as genetic algorithm (GA), particle swarm optimization (PSO), bat algorithm (BA), fuzzy logic et cetera [8], [21], [24]- [29].…”

Section: Introductionmentioning

confidence: 99%

Modelling and proportional-integral-derivative controller design for position analysis of the 3-degree of freedom

Budin

Osman

2022

IJEECS

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A closed-loop system or which can also be known as a feedback system helps the system to achieve the desired output by comparing the input and the output values. If any difference is detected, the closed-loop system will create an error signal and automatically responds to it. Other than that, the proportional-integral-derivative (PID) controller has a feedback mechanism. Thus, this creates the curiosity whether the closed-loop system and PID which both have the characteristic of a feedback system, can give the same. In this paper, the comparison of the model of 3 degree of freedom (DOF) Mitsubishi RV2-AJ is being made between two models of a robot arm that has a closed-loop system but only one that is embedded with PID controller while the other one is not, these two are simulated for different positions. The new model is created by using Solidworks which is later exported to Matlab-Simulink. The results from MATLAB-Simulink show that the model which is equipped with a PID controller has better results in terms of the rise time and percentage of overshoot. These results confirm the effectiveness of PID controller in producing smaller errors in the systems even when both models are created together with closed-loop systems.

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Fuzzy pid control of electromechanical actuator system

Cited by 9 publications

References 9 publications

Application of neural network algorithm in electromechanical automatic control system

Application of neural network algorithm in electromechanical automatic control system

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

Modelling and proportional-integral-derivative controller design for position analysis of the 3-degree of freedom

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