Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "Particle Swarm Optimization" wg kryterium: Temat


Wyświetlanie 1-6 z 6
Tytuł:
Particle swarm optimization of an iterative learning controller for the single-phase inverter with sinusoidal output voltage waveform
Autorzy:
Ufnalski, B.
Grzesiak, L. M.
Gałkowski, K.
Powiązania:
https://bibliotekanauki.pl/articles/200271.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
iterative learning control
sine wave inverter
particle swarm optimization (PSO)
Opis:
This paper presents the application of a particle swarm optimization (PSO) to determine iterative learning control (ILC) law gains for an inverter with an LC output filter. Available analytical tuning methods derived for a given type of ILC law are not very straightforward if additional performance requirements of the closed-loop system have to be met. These requirements usually concern the dynamics of a response to a reference signal, the dynamics of a disturbance rejection, the immunity against expected level of system and measurement noise, the robustness to anticipated variations of parameters, etc. An evolutionary optimization approach based on the swarm intelligence is proposed here. It is shown that in the case of the ILC applied to the LC filter, a cost function based on mean squares can produce satisfactory tuning effects. The efficacy of the procedure is illustrated by performing the optimization for various noise levels and various requested dynamics.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2013, 61, 3; 649-660
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Particle swarm optimization of artificial-neural-network-based on-line trained speed controller for battery electric vehicle
Autorzy:
Ufnalski, B.
Grzesiak, L.
Powiązania:
https://bibliotekanauki.pl/articles/201631.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
electric vehicle
speed control
adaptive ANN controller
particle swarm optimization (PSO)
Opis:
The paper presents implementation of PSO (Particle Swarm Optimization) to ANN-based speed controller tuning. Selected learning parameters are optimized according to the control objective function. A battery electric vehicle is considered as a potential plant for an adaptive speed controller. The need for adaptivity in the control algorithm is justified by variations of a total weight of the vehicle. A sizable section of the paper deals with selection of a combined objective function able to effectively evaluate the quality of a solution.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 661-667
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Grid-tied converter operated under unbalanced and distorted grid voltage conditions
Autorzy:
Gałecki, A.
Michalczuk, M.
Kaszewski, A.
Ufnalski, B.
Grzesiak, L. M.
Powiązania:
https://bibliotekanauki.pl/articles/200867.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
grid tied converter
AC/DC converter
current controller
resonant controller
particle swarm optimization (PSO)
Opis:
The paper presents a three-phase grid-tied converter operated under unbalanced and distorted grid voltage conditions, using a multi-oscillatory current controller to provide high quality phase currents. The aim of this study is to introduce a systematic design of the current control loop. A distinctive feature of the proposed method is that the designer needs to define the required response and the disturbance characteristic, rather than usually unintuitive coefficients of controllers. Most common approach to tuning a state-feedback controller use linear-quadratic regulator (LQR) technique or pole-placement method. The tuning process for those methods usually comes down to guessing several parameters. For more complex systems including multi-oscillatory terms, control system tuning is unintuitive and cannot be effectively done by trial and error method. This paper proposes particle swarm optimization to find the optimal weights in a cost function for the LQR procedure. Complete settings for optimization procedure and numerical model are presented. Our goal here is to demonstrate an original design workflow. The proposed method has been verified in experimental study at a 10 kW laboratory setup.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2020, 68, 2; 389-398
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Performance Study on Synchronous and Asynchronous Update Rules for A Plug-In Direct Particle Swarm Repetitive Controller
Autorzy:
Ufnalski, B.
Grzesiak, L. M.
Powiązania:
https://bibliotekanauki.pl/articles/141272.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
repetitive process control
particle swarm optimization (PSO)
synchronous and asynchronous update rules
dynamic optimization problem
repetitive disturbance rejection
optimal control
Opis:
In this paper two different update schemes for the recently developed plug-in direct particle swarm repetitive controller (PDPSRC) are investigated and compared. The proposed approach employs the particle swarm optimizer (PSO) to solve in on-line mode a dynamic optimization problem (DOP) related to the control task in the constant-amplitude constant-frequency voltage-source inverter (CACF VSI) with an LC output filter. The effectiveness of synchronous and asynchronous update rules, both commonly used in static optimization problems (SOPs), is assessed and compared in the case of PDPSRC. The performance of the controller, when synthesized using each of the update schemes, is studied numerically.
Źródło:
Archives of Electrical Engineering; 2014, 63, 4; 635-646
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid MPPT algorithm for PV systems under partially shaded conditions using a stochastic evolutionary search and a deterministic hill climbing
Autorzy:
Basiński, K.
Ufnalski, B.
Grzesiak, L. M.
Powiązania:
https://bibliotekanauki.pl/articles/1193446.pdf
Data publikacji:
2017
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
maximum power point tracking
photovoltaic system
hybrid part-stochastic part-deterministic search rule
particle swarm optimization (PSO)
partial shading
hill climbing
Opis:
A hybrid maximum power point tracking method has been proposed for the photovoltaic system using a stochastic evolutionary search and a deterministic hill climbing algorithm. The proposed approach employs the particle swarm optimizer (PSO) to solve a dynamic optimization problem related to the control task in a PV system. The position of the best particle is updated by the hill climbing algorithm, and the position of the rest of the particles by the classic PSO rule. The presented method uses the re-randomization mechanism, which places five consecutive particles randomly, but in specified intervals. This mechanism helps track the maximum power point under partially shaded conditions.
Źródło:
Power Electronics and Drives; 2017, 2, 37/2; 49-59
2451-0262
2543-4292
Pojawia się w:
Power Electronics and Drives
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Plug-in direct particle swarm repetitive controller with a reduced dimensionality of a fitness landscape – a multi-swarm approach
Autorzy:
Ufnalski, B.
Grzesiak, L. M.
Powiązania:
https://bibliotekanauki.pl/articles/202046.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
repetitive process control
dynamic optimization problem
particle swarm optimizer
repetitive disturbance rejection
noninteracting subswarms
dimension-reduced fitness functional
powtarzalne sterowanie procesem
problem optymalizacji dynamicznej
optymalizator rojem cząstek
odrzucanie zakłóceń
sprawność funkcjonalna
Opis:
The paper describes a modification to the recently developed plug-in direct particle swarm repetitive controller (PDPSRC) for the sine-wave constant-amplitude constant-frequency (CACF) voltage-source inverter (VSI). The original PDPSRC algorithm assumes that the particle swarm optimizer (PSO) takes into account a performance index defined over the whole reference signal period. Each particle stores all the samples of the control signal, e.g. α = 200 samples for a controller working at 10 kHz and the reference frequency equal to 50 Hz. Therefore, the fitness landscape (i.e. the performance index) is -dimensional ( D), which makes optimization challenging. That solution can be categorized as the single-swarm one. It has been previously shown that the swarm controller does not suffer from long-term stability issues encountered in the classic iterative learning controllers (ILC). However, the convergence of the swarm has to be kept at a relatively low rate to enable successful exploitation in the D search space, which in turn results in slow responsiveness of the PDPSRC. Here a multi-swarm approach is proposed in which we divide a dynamic optimization problem (DOP) among less dimensional swarms. The reference signal period is segmented into shorter intervals and the control signal is optimized in each interval independently by separate swarms. The effectiveness of the proposed approach is illustrated with the help of numerical experiments on the CACF VSI with an output LC filter operating under nonlinear loads.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 4; 857-866
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-6 z 6

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies