Multi-Objective Genetic Algorithm Optimization Using PID Controller for AQM/TCP Networks

Chebli, Samira; Elakkary, Ahmed; Sefiani, Nacer

doi:10.15866/ireaco.v10i1.11143

Cited by 6 publications

(7 citation statements)

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“…Thus, it can be shown that the ACO technic based on Pareto efficiency provides satisfactory results compared to the solutions given by GA and ZN methods used in previous research works (Chebli & Akkary, 2016;Chebli et al, 2017a) Table 2 and Figure 6 summarize this comparison. We took only one solution for each performance index since all the solutions are equivalent given that they belong to the Pareto surface, we chose the solutions which offer the smallest settling time and rise time.…”

Section: Simulation Results and Analysismentioning

confidence: 60%

“…It has been opted for this method to be compared with for its simplicity and efficiency (Åström & Hägglund, 1995). As for the GA optimization method, it is considered as a useful optimization method employing the principles of natural genetic systems (Chebli et al, 2017a;Goldberg & Holland, 1988) to seek a global solution of the optimization problem. GAs are stochastic optimization methods that sweep the entire admissible space to search the optimal solution.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…Natural processes are often at the basis of metaheuristics inspiration, namely simulated annealing (Metropolis, Rosenbluth, Rosenbluth, Teller, & Teller, 1953), genetic algorithms (GAs, Goldberg & Holland, 1988), particle swarm optimization (Fatih & Liang, 2007), and Ant Colony Optimization (Chebli et al, 2017a).…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

“…This solution consists in adopting an extension of the Hermite-Biehler theorem applied to quasi-polynomials. The principle of this theorem is used to stabilize the TCP model by means of a proportional-integral-derivative (PID) controller (Chebli, Elakkary, & Sefiani, 2017a, 2017bChebli, Elakkary, Sefiani, & Elalami, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Ant Colony Optimization based on Pareto optimality: application to a congested router controlled by PID regulation

Chebli

Elakkary

Sefiani

2018

Systems Science & Control Engineering

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The subject of this research work is to stabilize the network TCP (transmission control protocol) as well as the queue of the router congestion by designing an Active Queue Management scheme able to ensure this role. The problem is dealt with under the theory of the command by using a tuned PID (proportional-integral-derivative) controller based on an extension of the Hermite-Biehler theorem applied to quasi-polynomials. This tuning approach uses Hurwitz stability concept, that is to say, a sufficient and necessary condition must be given so the roots of the quasi-polynomial lie in the left half plane. Since this stabilization method gives rise to a set of values for parameters 'P', 'I' and 'D', it turns out relevant to optimize the results achieved within this stability region. To achieve this purpose, a multi-criterion Ant Colony Optimization based on Pareto optimality is used, given the conflictual character of the closed-loop system performance parameters. The set of optimal solutions of the problem is given by determining the Pareto front of objective functions. The effectiveness of the proposed control scheme is evaluated via a series of numerical simulations in MATLAB and SIMULINK. The results are compared with those of the genetic algorithm and Ziegler-Nichols methods.

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Section: Simulation Results and Analysismentioning

confidence: 60%

Section: Simulation Results and Analysismentioning

confidence: 99%

Section: Ant Colony Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Ant Colony Optimization based on Pareto optimality: application to a congested router controlled by PID regulation

Chebli

Elakkary

Sefiani

2018

Systems Science & Control Engineering

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“…Several advanced algorithms for computing the dropping probability were proposed to date, see, for example [ 4 , 5 , 6 , 7 ] and the references given there. Some propositions are based on artificial neural networks (e.g., [ 8 ]), fuzzy logic (e.g., [ 9 ]) or genetic algorithms (e.g., [ 10 ]). In others, the dropping probability is replaced by a deterministic decision about each arriving packet, i.e., whether to drop it, or not [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

On the Transient Queue with the Dropping Function

Chydziñski

2020

Entropy

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We deal with a queueing system, in which arriving packets are being dropped with the probability depending on the queue size. Such a scheme is used in several active queue management schemes proposed for Internet routers. In this paper, we derive and analyze a selected transient characteristic of the model, i.e., the probability that in a given time interval the queue size is kept under a predefined level. As the main purpose of the discussed queueing scheme is to maintain the queue size low, this is a natural characteristic to study. In addition to that, the average time to reach a given level is derived. Theoretical results for both characteristics are accompanied by numerical examples. Among other things, they demonstrate that the transient behavior of the queue may vary significantly with the shape of the dropping function, even if the steady-state performance remains unaltered.

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Multi-loop active disturbance rejection control and PID control strategy for poultry house based on GA, PSO and GWO algorithms

Elghardouf,

Ennaciri,

Elakkary

et al. 2024

Heliyon

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Multi-Objective Genetic Algorithm Optimization Using PID Controller for AQM/TCP Networks

Cited by 6 publications

References 0 publications

Ant Colony Optimization based on Pareto optimality: application to a congested router controlled by PID regulation

Ant Colony Optimization based on Pareto optimality: application to a congested router controlled by PID regulation

On the Transient Queue with the Dropping Function

Multi-loop active disturbance rejection control and PID control strategy for poultry house based on GA, PSO and GWO algorithms

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