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Tytuł:
A novel multi-objective discrete particle swarm optimization with elitist perturbation for reconfiguration of ship power system
Autorzy:
Zhang, L.
Sun, J.
Guo, C.
Powiązania:
https://bibliotekanauki.pl/articles/260215.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
shipboard power system
reconfiguration
multi-objective
discrete PSO
elitist perturbation
Opis:
A novel multi-objective discrete particle swarm optimization with elitist perturbation strategy (EPSMODPSO) is proposed and applied to solve the reconfiguration problem of shipboard power system(SPS). The new algorithm uses the velocity to decide each particle to move one step toward positive or negative direction to update the position. An elitist perturbation strategy is proposed to improve the local search ability of the algorithm. Reconfiguration model of SPS is established with multiple objectives, and an inherent homogeneity index is adopted as the auxiliary estimating index. Test results of examples show that the proposed EPSMODPSO performs excellent in terms of diversity and convergence of the obtained Pareto optimal front. It is competent to solve network reconfiguration of shipboard power system and other multi-objective discrete optimization problems.
Źródło:
Polish Maritime Research; 2017, S 3; 79-85
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Early prediction of remaining discharge time for lithium-ion batteries considering parameter correlation between discharge stages
Wczesne przewidywanie czasu pozostałego do rozładowania baterii litowo-jonowej z uwzględnieniem korelacji parametrów z różnych etapów procesu rozładowania
Autorzy:
Yu, Jinsong
Yang, Jie
Tang, Diyin
Dai, Jing
Powiązania:
https://bibliotekanauki.pl/articles/1365259.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
lithium-ion battery
parameter correlation
particle swarm optimization (PSO)
particle filter
remaining discharge time prognostics
bateria litowo-jonowa
korelacja parametrów
optymalizacja rojem cząstek
filtr cząsteczkowy
prognozowanie czasu do rozładowania
Opis:
In this paper, we propose a method for making early predictions of remaining discharge time (RDT) that considers information about future battery discharge process. Instead of analyzing the entire degradation process of a battery, as in the existing literature, we obtain the information about future battery condition by decomposing the discharge model into three stages, according to level of voltage loss. Correlation between model parameters at the first and last stages of discharge process allows the values of model parameters in the future to be used to predict the value of parameters at early stages of discharge. The particle swarm optimization (PSO) and particle filter (PF) algorithms are employed to update parameters when new voltage data is available. A case study demonstrates that the proposed approach predicts RDT more accurately than the benchmark PF-based prediction method, regardless of the degradation period of the battery.
W pracy zaproponowano metodę wczesnego przewidywania czasu pozostałego do rozładowania baterii (RDT), która uwzględnia informacje na temat przyszłego procesu jej rozładowywania. Zamiast analizować cały proces degradacji baterii, jak to ma miejsce w literaturze przedmiotu, wykorzystano informacje o przyszłym stanie baterii uzyskane na drodze podziału modelu procesu rozładowania na trzy etapy, według poziomu utraty napięcia. Korelacje między parametrami modelu uzyskanymi na pierwszym i ostatnim etapie procesu rozładowania baterii umożliwiają wykorzystanie przyszłych wartości parametrów do przewidywania wartości parametrów we wczesnych etapach rozładowania. Do aktualizacji parametrów zgodnie z napływającymi nowymi danymi napięciowymi wykorzystano algorytm optymalizacji rojem cząstek (PSO) i algorytm filtra cząsteczkowego (PF). Studium przypadku pokazuje, że proponowane podejście pozwala bardziej precyzyjnie prognozować RDT niż metoda prognozowania oparta na PF, niezależnie od okresu degradacji baterii.
Źródło:
Eksploatacja i Niezawodność; 2019, 21, 1; 81-89
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Coordinated control strategy for microgrid stability maintenance under isolated island operation
Autorzy:
Wu, Pan
Xu, Xiaowei
Powiązania:
https://bibliotekanauki.pl/articles/1841281.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
coordinated control
isolated island operation
microgrid
particle swarm optimization
Opis:
In this study, the inverter in a microgrid was adjusted by the particle swarm optimization (PSO) based coordinated control strategy to ensure the stability of the isolated island operation. The simulation results showed that the voltage at the inverter port reduced instantaneously, and the voltage unbalance degree of its port and the port of point of common coupling (PCC) exceeded the normal standard when the microgrid entered the isolated island mode. After using the coordinated control strategy, the voltage rapidly recovered, and the voltage unbalance degree rapidly reduced to the normal level. The coordinated control strategy is better than the normal control strategy.
Źródło:
Archives of Electrical Engineering; 2021, 70, 2; 285-295
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Particle swarm optimization and discrete artificial bee colony algorithms for solving production scheduling problems
Autorzy:
Witkowski, Tadeusz
Powiązania:
https://bibliotekanauki.pl/articles/298169.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Warmińsko-Mazurski w Olsztynie
Tematy:
Discrete Artificial Bee Colony
particle swarm optimization (PSO)
production scheduling problem
makespan
Opis:
This paper shows the use of Discrete Artificial Bee Colony (DABC) and Particle Swarm Optimization (PSO) algorithm for solving the job shop scheduling problem (JSSP) with the objective of minimizing makespan. The Job Shop Scheduling Problem is one of the most difficult problems, as it is classified as an NP-complete one. Stochastic search techniques such as swarm and evolutionary algorithms are used to find a good solution. Our objective is to evaluate the efficiency of DABC and PSO swarm algorithms on many tests of JSSP problems. DABC and PSO algorithms have been developed for solving real production scheduling problem too. The experiment results indicate that this problem can be effectively solved by PSO and DABC algorithms.
Źródło:
Technical Sciences / University of Warmia and Mazury in Olsztyn; 2019, 22(1); 61-74
1505-4675
2083-4527
Pojawia się w:
Technical Sciences / University of Warmia and Mazury in Olsztyn
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Spare parts allocation optimization in a multi-echelon support system based on multi-objective particle swarm optimization metod
Optymalizacja alokacji części zamiennych w wieloszczeblowym systemie wsparcia na podstawie metody wielokryterialnej optymalizacji rojem cząstek
Autorzy:
Wang, Y.
Zhao, J.
Jia, X.
Tian, Y.
Powiązania:
https://bibliotekanauki.pl/articles/301801.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
MOPSO
części zamienne
alokacja
optymalizacja
prawdopodobieństwo wsparcia
spare parts
allocation
optimization
support probability
Opis:
Optymalizacja alokacji części zamiennych w wieloszczeblowym systemie wspomagania stanowi trudne zagadnienie, które wymaga optymalizacji nieliniowej funkcji celu oraz zmiennych całkowitych. W niniejszej pracy, opracowano wielokryterialny model optymalizacyjny, który maksymalizuje prawdopodobieństwo wsparcia i minimalizuje jego koszty. W celu rozwiązania problemu optymalizacyjnego, wykorzystano ulepszoną metodę wielokryterialnej optymalizacji rojem cząstek (MOPSO). W metodzie tej wykorzystano techniki redukcji wymiarów oraz wielokryterialnej optymalizacji algorytmowej, które mogą poprawić efektywność metody MOPSO. Zasady proponowanej metody zilustrowano przykładem numerycznym.
Spare parts allocation optimization in a multi-echelon support system presents a difficult problem which involves non-linear objective function and integer variables to be optimized. In this paper, a multi-objective optimization model was developed, which maximizes support probability and minimizes support costs. In order to solve the optimization problem, an improved multi-objective particle swarm optimization (MOPSO) method was utilized. In this method, techniques of dimensions reduction and rules-based multi-objective optimization were employed, which can improve the efficiency of MOPSO method. A numerical example was given to show the performance of proposed method.
Źródło:
Eksploatacja i Niezawodność; 2014, 16, 1; 29-36
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An Analytical Study for the Role of Fuzzy Logic in Improving Metaheuristic Optimization Algorithms
Autorzy:
Vij, Sonakshi
Jain, Amita
Tayal, Devendra
Castillo, Oscar
Powiązania:
https://bibliotekanauki.pl/articles/385121.pdf
Data publikacji:
2018
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
fuzzy logic
metaheuristics
evolutionary computing
genetic algorithm
particle swarm optimization (PSO)
ant colony optimization
fuzzy evolutionary algorithm
fuzzy cuckoo
fuzzy simulated annealing
fuzzy swarm intelligence
fuzzy differential evolution
tabu
fuzzy mutation
fuzzy natural selection
fuzzy fitness function
big bang big crunch
fuzzy bacterial
neuro fuzzy logic
logika rozmyta
metaheurystyka
obliczenia ewolucyjne
algorytm genetyczny
optymalizacja roju cząstek
optymalizacja kolonii mrówek
Opis:
The research applications of fuzzy logic have always been multidisciplinary in nature due to its ability in handling vagueness and imprecision. This paper presents an analytical study in the role of fuzzy logic in the area of metaheuristics using Web of Science (WoS) as the data source. In this case, 178 research papers are extracted from it in the time span of 1989-2016. This paper analyzes various aspects of a research publication in a scientometric manner. The top cited research papers, country wise contribution, topmost organizations, top research areas, top source titles, control terms and WoS categories are analyzed. Also, the top 3 fuzzy evolutionary algorithms are extracted and their top research papers are mentioned along with their topmost research domain. Since neuro fuzzy logic poses feasible options for solving numerous research problems, hence a section is also included by the authors to present an analytical study regarding research in it. Overall, this study helps in evaluating the recent research patterns in the field of fuzzy metaheuristics along with envisioning the future trends for the same. While on one hand this helps in providing a new path to the researchers who are beginners in this field as they can start exploring it through the analysis mentioned here, on the other hand it provides an insight to professional researchers too who can dig a little deeper in this field using knowledge from this study.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 4; 11-27
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Power quality management in electrical grid using SCANN controller-based UPQC
Autorzy:
Varadharajan, Balaji
Subramanian, Chitra
Powiązania:
https://bibliotekanauki.pl/articles/2173547.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
SCANN
single comprehensive artificial neural network
UPQC
unified power quality conditioner
total harmonic distortion
particle swarm optimization
POS
sztuczna sieć neuronowa pojedyncza kompleksowa
zunifikowany kondycjoner jakości energii
współczynnik zawartości harmonicznych
optymalizacja roju cząstek
PSO
Opis:
The electrical grid integration takes great attention because of the increasing population in the nonlinear load connected to the power distribution system. This manuscript deals with the power quality issues and mitigations associated with the electrical grid. The proposed single comprehensive artificial neural network (SCANN) controller with unified power quality conditioner (UPQC) is modelled in MATLAB Simulink environment. It provides series and shunt compensation that helps mitigate voltage and current distortion at the end of the distribution system. Initially, four proportional integral (PI) controllers are used to control the UPQC. Later the trained SCANN controller replaces four PI Controllers for better control action. PI and SCANN controllers’ simulation results are compared to find the optimal solutions. A prototype model of SCANN controller is constructed and tested. The test results show that the SCANN based UPQC maintains grid voltage and current magnitude within permissible limits under fluctuating conditions.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 1; e140257, 1--9
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Toward the best combination of optimization with fuzzy systems to obtain the best solution for the GA and PSO algorithms using parallel processing
Autorzy:
Valdez, Fevrier
Kawano, Yunkio
Melin, Patricia
Powiązania:
https://bibliotekanauki.pl/articles/384329.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
genetic algorithms
particle swarm optimization (PSO)
fuzzy logic
parallel processing
Opis:
In general, this paper focuses on finding the best configuration for PSO and GA, using the different migration blocks, as well as the different sets of the fuzzy systems rules. To achieve this goal, two optimization algorithms were configured in parallel to be able to integrate a migration block that allow us to generate diversity within the subpopulations used in each algorithm, which are: the particle swarm optimization (PSO) and the genetic algorithm (GA). Dynamic parameter adjustment was also performed with a fuzzy system for the parameters within the PSO algorithm, which are the following: cognitive, social and inertial weight parameter. In the GA case, only the crossover parameter was modified.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 1; 55-64
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative Study of Particle Swarm Optimization and Genetic Algorithms for Complex Mathematical Functions
Autorzy:
Valdez, F.
Melin, P.
Powiązania:
https://bibliotekanauki.pl/articles/384575.pdf
Data publikacji:
2008
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
genetic algorithms
particle swarm optimization (PSO)
hybrid systems
optimization
Opis:
The Particle Swarm Optimization (PSO) and the Genetic Algorithms (GA) have been used successfully in solving problems of optimization with continuous and combinatorial search spaces. In this paper the results of the application of PSO and GAs for the optimization of mathematical functions are presented. These two methodologies have been implemented with the goal of making a comparison of their performance in solving complex optimization problems. This paper describes a comparison between a GA and PSO for the optimization of complex mathematical functions.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2008, 2, 1; 43-51
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
High quality repetitive control system for a grid-tied converter under distorted grid voltage conditions – design and implementation
Autorzy:
Ufnalski, Bartlomiej
Straś, Andrzej
Grzesiak, Lech M.
Powiązania:
https://bibliotekanauki.pl/articles/2090719.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
AC/DC power converter
current control
particle swarm optimization
power quality
repetitive control
RC
przetwornica mocy AC/DC
kontrola prądu
optymalizacja roju cząstek
jakość prądu
kontrola powtarzalna
Opis:
The paper features a grid-tied converter with a repetitive current controller. Our goal here is to demonstrate the complete design workflow for a repetitive controller, including phase lead, filtering and conditional learning. All key parameters, i.e., controller gain, filter and fractional phase lead, are designed in a single optimization procedure, which is a novel approach. The description of the design and optimization process, as well as experimental verification of the entire control system, are the most important contributions of the paper. Additionally, one more novelty in the context of power converters is verified in the physical system – a conditional learning algorithm to improve transient states to abrupt reference and disturbance changes. The resulting control system is tested experimentally in a 10 kW converter.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; e136739, 1--11
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
High quality repetitive control system for a grid-tied converter under distorted grid voltage conditions – design and implementation
Autorzy:
Ufnalski, Bartlomiej
Straś, Andrzej
Grzesiak, Lech M.
Powiązania:
https://bibliotekanauki.pl/articles/2173606.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
AC/DC power converter
current control
particle swarm optimization
power quality
repetitive control
RC
przetwornica mocy AC/DC
kontrola prądu
optymalizacja roju cząstek
jakość prądu
kontrola powtarzalna
Opis:
The paper features a grid-tied converter with a repetitive current controller. Our goal here is to demonstrate the complete design workflow for a repetitive controller, including phase lead, filtering and conditional learning. All key parameters, i.e., controller gain, filter and fractional phase lead, are designed in a single optimization procedure, which is a novel approach. The description of the design and optimization process, as well as experimental verification of the entire control system, are the most important contributions of the paper. Additionally, one more novelty in the context of power converters is verified in the physical system – a conditional learning algorithm to improve transient states to abrupt reference and disturbance changes. The resulting control system is tested experimentally in a 10 kW converter.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; art. no. e136739
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:
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:
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

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