Biogeography Based Optimization for Tuning FLC Controller of PMSM

Shneen, Salam Waley; Mao, Chengxiong; Bachache, Nasseer K.

doi:10.1007/978-3-319-20466-6_42

Cited by 7 publications

(8 citation statements)

References 12 publications

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“…Where: e t : The error signal between (the input reference and the process output) ec t : The change of error signal : Proportional constant gain : Integral constant gain The traditional PI controllers are used in many applications for position and speed control, these controller methods need for re-tuning its parameters because it sometimes does not give better tuning and inclines to produce a large overshoot. To boost the abilities of PI parameter tuning, different intelligent techniques have been proposed to improve the PI tuning such as genetic algorithms (GA) [39][40][41][42], biogeography based optimization (BBO) [43][44][45], ant colony optimization (ACO) [46], bee colony optimization (BCO) [47], and PSO. The technique PSO was proposed in this work to tune the PI controller parameters to reach closely an optimal performance of PI controller to reduce the effect of congestion in TCP networks, for more details about PSO technique you can review Refs, [48][49][50]…”

Section: Simulink Model For Tcp/aqm Systemmentioning

confidence: 99%

Design and implementation of a stability control system for TCP/AQM network

Shneen¹,

Sulttan

Oudah

2021

IJEECS

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In this work, we used a new approach as active queue management (AQM) to avoid data congestion in TCP/IP networks. The new approach is PSO-PI controller which use the proportional-integral controller as a control unit and particle swarm optimization (PSO) algorithm as an optimization technique to improve the performance of the PI controller and therefore improving the performance of TCP/IP networks as a required goal. The optimization control (PSO-PI) is characterized by access to design and choosing the optimal parameters of (K_1 and K_p) to reach optimal solutions in a short way (fewer iterations). The implementation of the PSO algorithm is achieving by using the mathematical system model and M-file and SIMULINK in Mathlab program. Simulation results show good congestion management performance with PSO-PI controller better than the PI controller as AQM in TCP networks, and the proposed method was very fast and required few iterations.

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Section: Simulink Model For Tcp/aqm Systemmentioning

confidence: 99%

Design and implementation of a stability control system for TCP/AQM network

Shneen¹,

Sulttan

Oudah

2021

IJEECS

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“…The requisite idea from GA is to preserve a population of conceivable solution that develops and evolves with time through rivalry process and controlled variance. The GA has performed well in various fields such as modelling, power goodness evaluation, resource allocation and, adaptive tabling system, etc [35][36][37].…”

Section:  Issn: 2088-8708mentioning

confidence: 99%

Proportional-integral genetic algorithm controller for stability of TCP network

Sulttan

Jaber

Shneen

2020

IJECE

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The life development and increase the number of internet users imposed an increase in data circulating on the internet network and then make the network more congestion. As a result of all this, some problems arose such as time delay in packets delivery, loss of packets, and exceed the buffer capacity for the middle routers. To overcome those problems, transmission control protocol and active queue management (TCP/AQM) have been used. AQM is the main approach used to control congestion and overcome those problems to improve network performance. This work proposes to use the proportional-integral (PI) controller with a genetic algorithm (GA) as an active queue manager for routers of the Internet. The simulation results show a good performance for managing the congestion with using proportional-integral genetic algorithm (GA-PI) controller better than the PI controller.

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“…Nevertheless, manufacturing highly effective semiconductor-switches results in production of high-speed response as well as high operating frequency of the DC-DC convector, which in consequence increases the application of such convertor in DC motor drive. Hence, driving the DC motor using the DC-DC convertor has gained consider attentions in many literatures [16]. Introduced 4th orders mathematical models for DC motor coupled with DC-DC convertor and PI controller to regulate the angular velocity of the motor.…”

Section: Introductionmentioning

confidence: 99%

Simulation model of proportional integral controller-PWM DC-DC power converter for DC motor using MATLAB

Shneen

Shuraiji²,

Hameed³

2023

IJEECS

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Smoothly speed range changing, easily speed controlling, and swiftly dynamic response for load torque changing are the main merits which are delivered by direct current (DC) motors. They are also distinguished by their versatility. All these characteristics make the DC motors suitable candidates for various applications. An accurate high-speed control with a good dynamic response, would be of demand for many applications of the DC motors. Controlling the speed of motors using conventional systems is one of the most important method that is adopted and it can be more efficient when used with electronic power devices to control the output voltage. Hence, this paper introduces an efficient proportional integral (PI) speed controller for DC motor fed by direct current-direct current (DC-DC) convertor, which is switched by pulse-width modulation technique. MATLAB/Simulink environment is used to build the whole system. Two operation scenarios have been conducted including constant load with variable speed and variable load with constant speed.

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Biogeography Based Optimization for Tuning FLC Controller of PMSM

Cited by 7 publications

References 12 publications

Design and implementation of a stability control system for TCP/AQM network

Design and implementation of a stability control system for TCP/AQM network

Proportional-integral genetic algorithm controller for stability of TCP network

Simulation model of proportional integral controller-PWM DC-DC power converter for DC motor using MATLAB

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