PID Control Of DC Motor Using Particle Swarm Optimization (PSO) Algorithm

Moghaddas, Mahbubeh; Dastranj, Mohamadreza; Changizi, Nemat; Rouhani, Modjtaba

doi:10.22436/jmcs.001.04.16

Cited by 7 publications

(8 citation statements)

References 7 publications

(9 reference statements)

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“…The best previously visited position of the ith particle is denoted as P = [p p …p ] . Defining ''g'' as the index of the best particle in the swarm, where the gth particle is the best, and let the superscripts denote the iteration number, then the swarm is manipulated according to the following two equations [26].…”

Section: Particle Swarm Optimization With Pidmentioning

confidence: 99%

“…Thought V has been found not to be necessary in the PSO with inertia version, however it can be useful and is suggested that a V =X be used [23][24][25][26][27]. The original procedure for implementing PSO is as follows: Fig.…”

Section: Typicallymentioning

confidence: 99%

“…The original procedure for implementing PSO is as follows: Fig. 3 Flow chart of PSO algorithm [26] In PID controller design methods, the most common performance criteria are integrated absolute error (IAE), the integrated of time weight square error (ITSE), integrated of squared error (ISE) and Mean Square Error (MSE) [28,29]. These four integral performance criteria have their own advantages and disadvantages.…”

Section: Typicallymentioning

confidence: 99%

See 2 more Smart Citations

Optimal PSO- PIλDμ Multi -Controller for a Robotic Wrist

Zennir

Mechhoud

Seboui

et al. 2018

AJSS

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Comparative study between to approach of control based in conventional PID controller and robust Fractional PID controller (FOPID) using PSO algorithm applied to control robotics wrist (Robot RX-90 Staübli). The mathematic model of robot are described follows by design of architecture control. two approximation method of fractional order are used and finally a different simulation study comparative between (PID, PSO-PID, FOPID and PSO-FOPID) with obtained results has been presented discussed and approved the efficiently of the architecture control with PSO-FOPID controller followed by a conclusion and some perspectives for future work.

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Section: Particle Swarm Optimization With Pidmentioning

confidence: 99%

Section: Typicallymentioning

confidence: 99%

Section: Typicallymentioning

confidence: 99%

See 1 more Smart Citation

Optimal PSO- PIλDμ Multi -Controller for a Robotic Wrist

Zennir

Mechhoud

Seboui

et al. 2018

AJSS

View full text Add to dashboard Cite

show abstract

“…System control model: Because the DC motor provides the driving force for the automatic side door system of EMU, the DC motor optimizing control is the automatic side door control core. Aiming the performance requirements for the operation of the automatic side door and combining with the features of automatic side door, the optimal control model of automatic side door system is established (Moghaddas et al, 2010). DC motor rotation speed model: DC motor rotation speed n can be expressed as Eq.…”

Section: Photoelectric Encodermentioning

confidence: 99%

Control Method of High-Speed Train Automatic Side Door Based on Gravitational Search Algorithm

Liu¹,

Yu²,

Guo³

et al. 2015

J. of Software Engineering

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The EMU has many characteristics, such as fast, safe, environmental protection and so on, which make it become the main means of transportation. Automatic side door is the channel for passengers pass in and out cars, is the most frequently used parts of passengers, the reliability and ease of its functions is closely related to with the passengers. In this study, aiming at the EMU automatic side door environment of the actual use and application characteristic, we propose a side door automatic optimization control method based on gravitational search algorithm for the optimal control of automatic side door. Firstly, this study analyzes the operating characteristics of the automatic side door and provides the basis for system control. Then, it establishes a mathematical model of the system control according to the rotating speed characteristic and torque characteristics of system drive device motor and then, the motor was controlled by optimizing PID control algorithm and PID parameters were optimized and solved by gravitational search algorithm. Finally, the proposed controlling method was verified by experiments, experimental results were shown that the method was feasible and could meet the precise control requirements of the automatic door of EMU.

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“…These animals include bees, ants, wasps, and find a behavioural algorithm from the habits or behaviour of these animals. This includes genetic algorithmic, huge bang-big crunch improvement, artificial bee colony, particle swarm optimization, bacterial foraging, and flower pollination [20,[22][23][24][25][26][27][28][29][30][31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Performance Optimization of Brushless DC Motors for the Mitigation of Voltage Dips, Swells and Short Interruptions in Weak Grids

Awad

Gouda

2020

ERJ. Engineering Research Journal

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Normally, BLDC motor drives a sensitive load which is severely influenced by disturbances such as voltage dips, swells, and short interruptions in weak grids. The main objective of this work is to investigate the performance of BLDC motors when they are tied to weak grids. Thus, this paper presents a study on the performance of BLDC motor considering disturbed utility conditions. Also, an efficient solution to guarantee a soft operation of a BLDC motor driving a sensitive load is presented. A buckboost DC converter is merged with the BLDC drive inverter to be able to mitigate voltage dips as well as voltage swells. A short interruption of one or two phases of the grid voltage can also be mitigated. The BLDC motor is controlled via a cascade PI-controller layout that has an outer loop for the speed control and inner loop for the DC voltage control. The PI controllers' gains are optimized by using the ant-colony optimization technique and then implemented in a simulation model using MATLAB/SIMULINK. Six cases of disturbances have been simulated including balanced and unbalanced dips, swells, and short interruption of one or two phases of the grid. Simulation results with various disturbances show the ability of the proposed controller to mitigate the grid disturbances with good transient and steady-state responses.

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PID Control Of DC Motor Using Particle Swarm Optimization (PSO) Algorithm

Cited by 7 publications

References 7 publications

Optimal PSO- PIλDμ Multi -Controller for a Robotic Wrist

Optimal PSO- PIλDμ Multi -Controller for a Robotic Wrist

Control Method of High-Speed Train Automatic Side Door Based on Gravitational Search Algorithm

Performance Optimization of Brushless DC Motors for the Mitigation of Voltage Dips, Swells and Short Interruptions in Weak Grids

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