Publications Internationales

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Subject: search.filters.subject.DC motor

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    Design of an optimally tuned fractionalized PID controller for DC mmotor speed control via a henry gas solubility optimization algorithm
    (Intelligent Network and Systems Society, 2022) Abdelhakim, Idir; Khettab, Khatir; Bensafia, Yassine
    The goal of this research is to develop a high-performance fractionalized proportional-integral-derivative (FPID) controller based on Henry Gas Solubility Optimization (HGSO) for controlling the speed of a direct current (DC) motor. The suggested HGSOA-based Fractionalized PID technique with Matsuda approximation method was used to obtain the optimal FPID controller by minimising the integral of time multiplied absolute error (ITAE) as the objective function. Index of performance and disturbance rejection analyses, as well as transient and frequency responses, were all employed to validate the suggested approach's effectiveness. The proposed HGSO-FPID controller with Matsuda approximation was then compared not only to the original HGSO algorithm-tuned PID controller, but also to other controllers tuned by cutting-edge meta-heuristic algorithms such as Atom Search Optimization algorithm (ASO), Grey Wolf Optimization algorithm (GWO), Particle Swarm Optimisation (PSO), Invasive Weed Optimisation (IWO), and stochastic fractal search (SFS). The results showed that the proposed HGSOA-FPID controller has better performance with lower settling time, Ts which 0.1003 s, with lower rise time, Tr which is 0.0579 s, negligible overshoot, D which is 0.0052% and strong output disturbance rejection when compared to the performance of the other controllers
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    Speed control of DC motor using PID and FOPID controllers based on differential evolution and PSO
    (INASS, 2018) Idir, Abdelhakim; Kidouche, Madjid; Bensafia, Yassine
    DC motors are widely used in industrial application for its different advantage such us high efficiency, low costs and flexibilities. For controlling the speed of DC motor, conventional controller PI and PID were the most widely used controllers. But due to empirically selected parameters 𝐾𝑝,𝐾𝑖,𝐾𝑑 and limitation of convention PID controller to achieve ideal control effect for higher order systems, a Fractional order Proportional-Integral-Derivative PID (FOPID) based on optimization techniques was proposed in this paper. The aim of this paper is to study the tuning of a FOPID controller using intelligent soft computing techniques such as Differential Evolution (DE) and Particle Swarm Optimization (PSO) for designing fractional order PID controller. The parameters of FOPID controller are determined by minimizing the Integral Time Absolute Error (ITAE) between the output of reference model and the plant. The performance of DE and PSO were compared with several simulation experiments. The simulation results show that the DE-based FOPID controller tuning approach provides improved performance for the setpoint tracking, error minimization, and measurement noise attenuation