Design an Optimal Fractional Order PI Controller for Congestion Avoidance in Internet Routers

Abood, Layla H.; Haitham, Russul

doi:10.18280/mmep.090521

Cited by 8 publications

(4 citation statements)

References 24 publications

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“…PID controllers is regarded as a simple and classical controllers that adopted for improving system behavior. Nowadays, studies are made with a different changes for PID controller like combining it with a neural network [19,20] or changing its structure to reach to a best stability and robustness as in [21,22] or changing it by add a fractional variables (integral & derivative) to the classical PID to improve system output [23,24], this type of change is an augmented type PID controller. These parameters (μ for derivative variable and λ for the integral variable) make the gains of controller be five variables.…”

Section: Fopid Controllermentioning

confidence: 99%

Design an Optimal Fractional Order PID Controller for Speed Control of Electric Vehicle

Kadhim,

Abood,

Mohammed

2023

JESA

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In recent years, electric vehicles have garnered significant attention due to their environmental and economic advantages compared to conventional vehicles, including reduced emissions and lower fuel costs. This study proposes an optimal fractional-order PID (FOPID) controller to regulate electric vehicle (EV) speed. The FOPID controller is advantageous due to its ability for stabilizing the system, managing parameter variations, and mitigating potential disturbances. The tuning of this controller's gains is achieved through an intelligent Ant Colony Optimization (ACO) algorithm. The selection of the gain values is strategically based on minimizing error, thereby ensuring a robust system response without overshoot or undershoots. The performance of the proposed controller is analyzed and compared to a classical PID controller for demonstrating its superior performance. Simulation results illustrate the efficiency of the proposed controller, which exhibits no fluctuation or oscillation in its response (zero overshoot) and fast settling and rise times of 0.0476 and 0.0297, respectively. By using the optimal gains determined by the smart ACO, the proposed controller achieves a satisfactory and robust system response in controlling EV speed.

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Section: Fopid Controllermentioning

confidence: 99%

Design an Optimal Fractional Order PID Controller for Speed Control of Electric Vehicle

Kadhim,

Abood,

Mohammed

2023

JESA

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“…Moreover, according to the results mentioned above and discussions, we have observed a significant difference between the performance of P and PI controllers on the vehicle speed with superiority registered for the PI controller. Indeed, it would be more interested in acquiring the PI controller as it rapidly converges to the desired velocity [15]. Finally, recall the stateful continuous-time component model of how the speed of a vehicle changes because of the force applied to it by the engine [7] when the vehicle is moving on an uphill single-dimension graded road.…”

Section: Ctc For Dynamic Vehicle Model With Pid Controllermentioning

confidence: 99%

Analytical Study for Cyber Dynamic Continuous Time Vehicle Model with Networked PID Controller

Al‐Haija¹

2022

MMEP

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This paper uses different physical scenarios to analyze the cyber dynamic continuous time vehicle model with a networked PID controller. First, we model the problem of stateful continuous-time components for the dynamic physical vehicle motion on a graded and flat road without using a PID controller. Second, we model the problem of stateful continuous-time components for the dynamic physical vehicle motion on a graded road using a PID controller in different specification scenarios. Third, we model the problem of stateful continuous-time components for the cyber-physical dynamic vehicle model motion using a networked PID controller at different specification scenarios. The simulation results indicated the superiority and efficacy of the cyber-physical dynamic vehicle model providing high stability and controllability in the vehicle motion using a PID controller and Transceiver (network node).

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“…In the study [4], a Tree-Seed Algorithm (TSA) is used for tuning PID gains and various tests are done to verify system response and enhance system tracking until reach to a stable level while in the study [5], a two optimization method is hybridized together the Simulated Annealing (SA) and Gorilla Troops Optimization (GTO) with a novel cost function is adopted for best optimal values choice. Other studies proposes the generalized form of PID controller which is named the Fractional order PID (FOPID) controller in this type of controller gains will be five parameters, two values are added with a fractional values [6,7], Ayas and Sahin [8] suggest a novel FOPID controller combined with fractional filter which increase controller gains to seven parameters which are all tuned using Sine Cosine Algorithm(SCA) and its compared with different classical controller then two analysis is done one of them is done by changing AVR system parameter and the other is done by applying external disturbances while in Mok and Ahmad [9] a modified smoothed function algorithm (MSFA) is proposed with the FOPID controller to enhance system regulating facility based on different objective functions.…”

Section: Introductionmentioning

confidence: 99%

Performance Evolution of Different Optimal Controllers for Controlling AVR System

Mohamed,

Abood

2023

JESA

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The main issue in electrical system is providing a stable voltage values in order to obtain best devices performance for this reason controlling the automatic voltage regulation (AVR) system becoma more helpful to achieve this requirments, in this paper three controllers are suggested for maintaining the terminal voltage level value of the generator part in AVR system that supplied to custumers, these controllers are (Conventional PID, ArcTan PID and Nonlinear PID), all gains of these controllers is tuned by using an intelligent sun flower optimization (SFO) algorithm. The objective of the design is finding suitable values of these gains that give a stable response based on minimizing error value and testing it using the Integral Time Absolute Error (ITAE) fitness function, the numerical results exhibited that the ArcTan PID controller give the best results values with a lower settling time (0.698) and its faster than conventional PID 5.034 % and faster than nonlinear PID by 5.163% for 5 second simulation time also its reach its peak value in 0.513 sec. and an expectable overshoot value equal to 0.513 with a small error value (0.000645) at its steady state case and then small error value when working at normal state without any disturbance or any uncertainty cases applied but when a disturbances signal is applied with a value equal to ± 0.3 to the system, the NLPID and the conventional PID presents a best response by returning the system to its desired value in just 2 second in the two cases applied and when change the gain values of two parts of AVR system( amplifier & sensor) the NLPID behaves as a the more suitable one and give a superior robust performance in facing this unwanted signals and then a desired response is achieved after small period time with satisfied and acceptable values for woring in this enviroment.

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Design an Optimal Fractional Order PI Controller for Congestion Avoidance in Internet Routers

Cited by 8 publications

References 24 publications

Design an Optimal Fractional Order PID Controller for Speed Control of Electric Vehicle

Design an Optimal Fractional Order PID Controller for Speed Control of Electric Vehicle

Analytical Study for Cyber Dynamic Continuous Time Vehicle Model with Networked PID Controller

Performance Evolution of Different Optimal Controllers for Controlling AVR System

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