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Wyszukujesz frazę "particle swarm optimization algorithm" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Design of a Predictive PID Controller Using Particle Swarm Optimization
Autorzy:
Mustafa, Norhaida
Hashim, Fazida Hanim
Powiązania:
https://bibliotekanauki.pl/articles/1844451.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
proportional integral derivative controller
particle swarm optimization (PSO) algorithm
optimization
predictive PID
Opis:
The proportional-integral-derivative (PID) controller is widely used in various industrial applications such as process control, motor drives, magnetic and optical memory, automotive, flight control and instrumentation. PID tuning refers to the generation of PID parameters (Kp, Ki, Kd) to obtain the optimum fitness value for any system. The determination of the PID parameters is essential for any system that relies on it to function in a stable mode. This paper proposes a method in designing a predictive PID controller system using particle swarm optimization (PSO) algorithm for direct current (DC) motor application. Extensive numerical simulations have been done using the Mathwork’s Matlab simulation environment. In order to gain full benefits from the PSO algorithm, the PSO parameters such as inertia weight, iteration number, acceleration constant and particle number need to be carefully adjusted and determined. Therefore, the first investigation of this study is to present a comparative analysis between two important PSO parameters; inertia weight and number of iteration, to assist the predictive PID controller design. Simulation results show that inertia weight of 0.9 and iteration number 100 provide a good fitness achievement with low overshoot and fast rise and settling time. Next, a comparison between the performance of the DC motor with PID-PSO, with PID of gain 1, and without PID were also discussed. From the analysis, it can be concluded that by tuning the PID parameters using PSO method, the best gain in performance may be found. Finally, when comparing between the PID-PSO and its counterpart, the PI-PSO, the PID-PSO controller gives better performance in terms of robustness, low overshoot (0.005%), low minimum rise time (0.2806 seconds) and low settling time (0.4326 seconds).
Źródło:
International Journal of Electronics and Telecommunications; 2020, 66, 4; 737-743
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of electric and magnetic field intensities in proximity of power lines using genetic and particle swarm algorithms
Autorzy:
Król, K.
Machczyński, W.
Powiązania:
https://bibliotekanauki.pl/articles/141588.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
power line
electric field
magnetic field
optimization
genetic algorithm
particle swarm algorithm
Opis:
The paper presents optimization of power line geometrical parameters aimed to reduce the intensity of the electric field and magnetic field intensity under an overhead power line with the use of a genetic algorithm (AG) and particle swarm optimization (PSO). The variation of charge distribution along the conductors as well as the sag of the overhead line and induced currents in earth wires were taken into account. The conductor sag was approximated by a chain curve. The charge simulation method (CSM) and the method of images were used in the simulations of an electric field, while a magnetic field were calculated using the Biot–Savart law. Sample calculations in a three-dimensional system were made for a 220 kV single – circuit power line. A comparison of the used optimization algorithms was made.
Źródło:
Archives of Electrical Engineering; 2018, 67, 4; 829-843
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Allocation of real power generation based on computing over all generation cost: an approach of Salp Swarm Algorithm
Autorzy:
Devarapalli, Ramesh
Sinha, Nikhil Kumar
Rao, Bathina Venkateswara
Knypiński, Łukasz
Lakshmi, Naraharisetti Jaya Naga
García Márquez, Fausto Pedro
Powiązania:
https://bibliotekanauki.pl/articles/1841291.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
economic load dispatch
heuristic algorithms
optimization
Particle Swarm
Algorithm
Salp Swarm Algorithm
ekonomiczna wysyłka ładunku
algorytmy heurystyczne
optymalizacja
rój cząstek
algorytm
Opis:
Economic Load Dispatch (ELD) is utilized in finding the optimal combination of the real power generation that minimizes total generation cost, yet satisfying all equality and inequality constraints. It plays a significant role in planning and operating power systems with several generating stations. For simplicity, the cost function of each generating unit has been approximated by a single quadratic function. ELD is a subproblem of unit commitment and a nonlinear optimization problem. Many soft computing optimization methods have been developed in the recent past to solve ELD problems. In this paper, the most recently developed population-based optimization called the Salp Swarm Algorithm (SSA) has been utilized to solve the ELD problem. The results for the ELD problem have been verified by applying it to a standard 6-generator system with and without due consideration of transmission losses. The finally obtained results using the SSA are compared to that with the Particle Swarm Optimization (PSO) algorithm. It has been observed that the obtained results using the SSA are quite encouraging.
Źródło:
Archives of Electrical Engineering; 2021, 70, 2; 337-349
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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