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


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DOI: https://doi.org/10.15866/ireaco.v10i1.11143

Abstract


The competition of connected sources to access to the resources within a network leads to a congestion that causes a global delay in the network. For this reason, it's challenging to design an optimized controller that stabilizes the system and reduces the present delay. This paper proposed a developed PID (Proportional Integral Derivative) controller based on an extension of Hermite-Biehler theorem applicable to quasipolynomials, that is to say to systems with delay. Then the stability region of the PID controller parameters was obtained. An improved Multi-objective Genetic Algorithm (GA) is employed to seek the optimal PID controller gains such that performance indices of integrated-absolute error (IAE), integrated-squared error (ISE), integrated-time-absolute error (ITAE) and integrated-time-squared error (ITSE) are minimized, and thereby a stability of TCP (Transmission Control Protocol)network is guaranteed. The performance of the proposed control scheme is evaluated via a series of numerical simulations that show its efficiency.
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Keywords


Multi-Objective Optimization; Pareto Optimality; MOGA; AQM; Congestion Control; Genetic Algorithm (GA); Hermite-Biehler Theorem; PID Controller; Time Delay Systems

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References


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