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Tytuł:
Robust L2 consensus of high-order swarm systems with time-varying delays
Autorzy:
Xi, J
Yao, Z
Liu, G.
Zhong, Y.
Powiązania:
https://bibliotekanauki.pl/articles/205770.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
consensus
swarm system
uncertainty
time delay
disturbance rejection
Opis:
Consensus problems for high-order continuous-time swarm systems in directed networks with time delays, uncertainties and external disturbances are investigated. Firstly, the state space of a swarm system is decomposed into a consensus subspace (CS) and a complement consensus space (CCS). A necessary and sufficient condition for the system with time delays and uncertainties to achieve consensus is presented based on the state projection on CCS, and an explicit expression of the consensus function is shown on the basis of the state projection on CS. Then, a sufficient condition for the system to achieve consensus with a desired L2 performance is given. Finally, numerical simulations are shown to demonstrate theoretical results.
Źródło:
Control and Cybernetics; 2014, 43, 1; 59-77
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
System rozpoznawczo-uderzeniowy SWARM
Autorzy:
Maciejewski, Adam M.
Powiązania:
Wojsko i Technika 2020, nr 10, s. 10-11
Data publikacji:
2020
Tematy:
WB Electronics (Ożarów Mazowiecki)
Wojska lądowe
Jednostki specjalne
Jednostki rozpoznania
System bezzałogowy
System rozpoznawczo-uderzeniowy
Dane taktyczno-techniczne sprzętu wojskowego
SWARM (system)
Artykuł z czasopisma fachowego
Artykuł z czasopisma wojskowego
Opis:
Artykuł dotyczy zintegrowanego systemu rozpoznawczo-uderzeniowego SWARM, który stworzyła polska Grupa WB. System opracowano głównie dla jednostek specjalnych i rozpoznania oraz formacji aeromobilnych lub spadochronowych. Omówiono elementy i strukturę systemu, dane taktyczno-techniczne oraz sposób działania. W założeniu SWARM ma być lekkim i prostym w użyciu narzędziem umożliwiającym jednoczesne wykrywanie, identyfikację i precyzyjne atakowanie celów punktowych.
Fotografie.
Dostawca treści:
Bibliografia CBW
Artykuł
Tytuł:
Overhead vision system for testing swarms and groups of wheeled robots
Autorzy:
Wiech, Jakub
Hendzel, Zenon
Powiązania:
https://bibliotekanauki.pl/articles/384852.pdf
Data publikacji:
2019
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
swarm robotics
vision system
wheeled robots
Opis:
The paper describes how to use ArUco markers to determine the position and orientation of wheeled robots in 3D space. it is preceded by a general description on the testbed and a detailed description on the marker detection algorithm along with the camera calibration using the ChaArUco markers. The camera has been described and calibrated using the pinhole camera model, taking into account distortion on the lens. The second part oo the article describes the wheeled robots with their mechanical construction.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2019, 13, 2; 15-22
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on resilience model of UAV swarm based on complex network dynamics
Autorzy:
Wei, Kunlun
Zhang, Tao
Chuanfu, Zhang
Powiązania:
https://bibliotekanauki.pl/articles/28328275.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
UAV swarm
resilience
SIS
system dynamics
topology
Opis:
Unmanned Aerial Vehicle (UAV) swarms are utilized in various missions and operated within an open environment that is prone to disruptions. The resilience of UAV swarms, an important requirement, mainly revolves around ensuring stable and uninterrupted operations. Malicious attacks can implement the adverse impacts of potential threats through swarm communication links. In this context, the SIS (Susceptible → Infected → Susceptible) method is suitable for describing the information transmission within UAV swarms. An enhanced resilience model of the UAV swarm is proposed in this study, which incorporates the factors of self-dynamics, dynamics of topology, dynamics of information transmission, and SIS into the complex network model. Self-dynamics refer to the internal dynamics of the drones. In this paper, dynamics of topology consist of three factors: the varying distance between drones, the incoming degrees of each drone, and the number of communication types between drones. Lastly, dynamics of information transmission are characterized by SIS. The model proposed in this paper has the capability to effectively capture changes in the network topology as well as the dynamics of the system, which are significant contributors to the loss of resilience. And then, the average number of susceptible drones is utilized as the metric to evaluate the resilience of the swarm. Furthermore, an experiment is conducted where a UAV swarm successfully carries out a surveillance mission to demonstrate the advantages of our proposed method. The proposed model not only enables the support of mission planning but also facilitates the design enhancements of UAV swarms.
Źródło:
Eksploatacja i Niezawodność; 2023, 25, 4; art. no. 173125
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Function optimization using metaheuristics
Autorzy:
Pilski, M.
Seredyński, F.
Powiązania:
https://bibliotekanauki.pl/articles/92887.pdf
Data publikacji:
2006
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
particle swarm optimization (PSO)
artificial immune system
genetic algorithm
function optimization
Opis:
The paper presents the results of comparison of three metaheuristics that currently exist in the problem of function optimization. The first algorithm is Particle Swarm Optimization (PSO) - the algorithm has recently emerged. The next one is based on a paradigm of Artificial Immune System (AIS). Both algorithms are compared with Genetic Algorithm (GA). The algorithms are applied to optimize a set of functions well known in the area of evolutionary computation. Experimental results show that it is difficult to unambiguously select one best algorithm which outperforms other tested metaheuristics.
Źródło:
Studia Informatica : systems and information technology; 2006, 1(7); 77-91
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Power system oscillation damping controller design: a novel approach of integrated HHO-PSO algorithm
Autorzy:
Devarapalli, Ramesh
Kumar, Vikash
Powiązania:
https://bibliotekanauki.pl/articles/1845528.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Harris hawk optimization
power system stabilizers
STATCOM
FACTS
particle swarm optimization
Opis:
The hybridization of a recently suggested Harris hawk’s optimizer (HHO) with the traditional particle swarm optimization (PSO) has been proposed in this paper. The velocity function update in each iteration of the PSO technique has been adopted to avoid being trapped into local search space with HHO. The performance of the proposed Integrated HHO-PSO (IHHOPSO) is evaluated using 23 benchmark functions and compared with the novel algorithms and hybrid versions of the neighbouring standard algorithms. Statistical analysis with the proposed algorithm is presented, and the effectiveness is shown in the comparison of grey wolf optimization (GWO), Harris hawks optimizer (HHO), barnacles matting optimization (BMO) and hybrid GWO-PSO algorithms. The comparison in convergence characters with the considered set of optimization methods also presented along with the boxplot. The proposed algorithm is further validated via an emerging engineering case study of controller parameter tuning of power system stability enhancement problem. The considered case study tunes the parameters of STATCOM and power system stabilizers (PSS) connected in a sample power network with the proposed IHHOPSO algorithm. A multi-objective function has been considered and different operating conditions has been investigated in this papers which recommends proposed algorithm in an effective damping of power network oscillations.
Źródło:
Archives of Control Sciences; 2021, 31, 3; 553-591
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Power system oscillation damping controller design: a novel approach of integrated HHO-PSO algorithm
Autorzy:
Devarapalli, Ramesh
Kumar, Vikash
Powiązania:
https://bibliotekanauki.pl/articles/1845539.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Harris hawk optimization
power system stabilizers
STATCOM
FACTS
particle swarm optimization
Opis:
The hybridization of a recently suggested Harris hawk’s optimizer (HHO) with the traditional particle swarm optimization (PSO) has been proposed in this paper. The velocity function update in each iteration of the PSO technique has been adopted to avoid being trapped into local search space with HHO. The performance of the proposed Integrated HHO-PSO (IHHOPSO) is evaluated using 23 benchmark functions and compared with the novel algorithms and hybrid versions of the neighbouring standard algorithms. Statistical analysis with the proposed algorithm is presented, and the effectiveness is shown in the comparison of grey wolf optimization (GWO), Harris hawks optimizer (HHO), barnacles matting optimization (BMO) and hybrid GWO-PSO algorithms. The comparison in convergence characters with the considered set of optimization methods also presented along with the boxplot. The proposed algorithm is further validated via an emerging engineering case study of controller parameter tuning of power system stability enhancement problem. The considered case study tunes the parameters of STATCOM and power system stabilizers (PSS) connected in a sample power network with the proposed IHHOPSO algorithm. A multi-objective function has been considered and different operating conditions has been investigated in this papers which recommends proposed algorithm in an effective damping of power network oscillations.
Źródło:
Archives of Control Sciences; 2021, 31, 3; 553-591
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Jacking and energy consumption control over network for jack-up rig: simulation and experiment
Autorzy:
Do, Viet-Dung
Dang, Xuan-Kien
Tran, Tien-Dat
Pham, Thi Duyen-Anh
Powiązania:
https://bibliotekanauki.pl/articles/32912855.pdf
Data publikacji:
2022
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
networked control system
environmental forces
energy consumption
Fuzzy Particle Swarm Optimization
jacking system
time-delay
Opis:
Oil and gas projects differ from regular investment projects in that they are frequently large-scale, categorised as vital national projects, highly technological, and associated with significant risks. Drilling rigs are a crucial component of the oil and gas sector and the majority of the systems and equipment aboard drilling rigs are operated automatically. Consequently, it is crucial to address the topic of an advanced control theory for off-shore systems. Network technology connected to control is progressively being used to replace outdated technologies, together with other contemporary technologies. In this study, we examine how to adapt a networked control jacking system to the effects of internal and external disturbances with a time delay, using a Fuzzy controller (FC)-based particle swarm optimisation. To demonstrate the benefit of the proposed approach, the developed Fuzzy Particle Swarm Optimisation (FPSO) controller is compared with the fuzzy controller. Finally, the results from simulations and experiments utilising Matlab software and embedded systems demonstrate the suitability of the proposed approach.
Źródło:
Polish Maritime Research; 2022, 3; 89-98
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
FLC control for tuning exploration phase in bio-inspired metaheuristic
Autorzy:
Kiełkowicz, K.
Grela, D.
Powiązania:
https://bibliotekanauki.pl/articles/106299.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Marii Curie-Skłodowskiej. Wydawnictwo Uniwersytetu Marii Curie-Skłodowskiej
Tematy:
Bat algorithm
swarm intelligence
metaheuristics
optimization
fuzzy logic
Mamdami-Type inference system
Opis:
Growing popularity of the Bat Algorithm has encouraged researchers to focus their work on its further improvements. Most work has been done within the area of hybridization of Bat Algorithm with other metaheuristics or local search methods. Unfortunately, most of these modifications not only improves the quality of obtained solutions, but also increases the number of control parameters that are needed to be set in order to obtain solutions of expected quality. This makes such solutions quite impractical. What more, there is no clear indication what these parameters do in term of a search process. In this paper authors are trying to incorporate Mamdani type Fuzzy Logic Controller (FLC) to tackle some of these mentioned shortcomings by using the FLC to control the exploration phase of a bio-inspired metaheuristic. FLC also allows us to incorporate expert knowledge about the problem at hand and define expected behaviors of system – here process of searching in multidimensional search space by modeling the process of bats hunting for their prey.
Źródło:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica; 2016, 16, 2; 32-38
1732-1360
2083-3628
Pojawia się w:
Annales Universitatis Mariae Curie-Skłodowska. Sectio AI, Informatica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent financial time series forecasting: A complex neuro-fuzzy approach with multi-swarm intelligence
Autorzy:
Li, C.
Chiang, T. W.
Powiązania:
https://bibliotekanauki.pl/articles/331280.pdf
Data publikacji:
2012
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
zbiór rozmyty
system neuronowo-rozmyty
optymalizacja rojem cząstek
szereg czasowy
complex fuzzy set
complex neuro fuzzy system
hierarchical multi swarm
particle swarm optimization (PSO)
recursive least squares estimator
time series forecasting
Opis:
Financial investors often face an urgent need to predict the future. Accurate forecasting may allow investors to be aware of changes in financial markets in the future, so that they can reduce the risk of investment. In this paper, we present an intelligent computing paradigm, called the Complex Neuro-Fuzzy System (CNFS), applied to the problem of financial time series forecasting. The CNFS is an adaptive system, which is designed using Complex Fuzzy Sets (CFSs) whose membership functions are complex-valued and characterized within the unit disc of the complex plane. The application of CFSs to the CNFS can augment the adaptive capability of nonlinear functional mapping, which is valuable for nonlinear forecasting. Moreover, to optimize the CNFS for accurate forecasting, we devised a new hybrid learning method, called the HMSPSO-RLSE, which integrates in a hybrid way the so-called Hierarchical Multi-Swarm PSO (HMSPSO) and the well known Recursive Least Squares Estimator (RLSE). Three examples of financial time series are used to test the proposed approach, whose experimental results outperform those of other methods.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2012, 22, 4; 787-800
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
PSO based optimal location and sizing of SVC for novel multiobjective voltage stability analysis during N – 2 line contingency
Autorzy:
Mangaiyarkarasi, S. P
Sree Renga Raja, T.
Powiązania:
https://bibliotekanauki.pl/articles/140430.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
N – 2 contingency analysis
voltage severity
particle swarm optimization (PSO)
SVC
power system planning
Opis:
In this paper voltage stability is analysed based not only on the voltage deviations from the nominal values but also on the number of limit violating buses and severity of voltage limit violations. The expression of the actual state of the system as a numerical index like severity, aids the system operator in taking better security related decisions at control centres both during a period of contingency and also at a highly stressed operating condition. In contrary to conventional N – 1 contingency analysis, Northern Electric Reliability Council (NERC) recommends N – 2 line contingency analysis. The decision of the system operator to overcome the present contingency state of the system must blend harmoniously with the stability of the system. Hence the work presents a novel N – 2 contingency analysis based on the continuous severity function of the system. The study is performed on 4005 possible combinations of N – 2 contingency states for the practical Indian Utility 62 bus system. Static VAr Compensator is used to improve voltage profile during line contingencies. A multi- objective optimization with the objective of minimizing the voltage deviation and also the number of limit violating bus with optimal location and optimal sizing of SVC is achieved by Particle Swarm Optimization algorithm.
Źródło:
Archives of Electrical Engineering; 2014, 63, 4; 535-550
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Setpoint weighted PID controller tuning for unstable system using heuristic algorithm
Autorzy:
Rajinikanth, V.
Latha, K.
Powiązania:
https://bibliotekanauki.pl/articles/229344.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
setpoint weighted PID
unstable system
particle swarm optimization (PSO)
bacterial foraging optimization
objective function
Opis:
Most of the real time chemical process loops are unstable in nature and designing a suitable controller for such systems are difficult than open loop stable processes. In this work, an attempt is made with a two degree of freedom setpoint weighted PID controller tuning procedure for a class of unstable systems using the recent heuristic algorithms such as Particle Swarm Optimization and Bacterial Foraging Optimization. The problem considered in this study is to aptly tune the controller in order to enhance the overall closed loop performance. A novel objective function proposed in this study is used to monitor the heuristic algorithms in order to get the optimal controller parameters like Kp, Ki, Kd, and alpha with minimized iteration number. The proposed method is validated with a simulation study and this helps to accomplish enhanced system performance such as smooth reference tracking, satisfactory disturbance rejection, and error minimization for a class of unstable systems.
Źródło:
Archives of Control Sciences; 2012, 22, 4; 481-505
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Coordinated control of phase shifting transformers in the power system
Skoordynowane sterowanie przesuwnikami fazowymi w systemie elektroenergetycznym
Autorzy:
Korab, R.
Owczarek, R.
Połomski, M.
Powiązania:
https://bibliotekanauki.pl/articles/397322.pdf
Data publikacji:
2017
Wydawca:
ENERGA
Tematy:
power system
phase shifting transformer
unscheduled flow
particle swarm optimisation
system elektroenergetyczny
przesuwnik fazowy
przepływ nieplanowy
optymalizacja rojem cząstek
Opis:
In response to the growing problem of unscheduled flows, more and more transmission system operators in Europe provide their systems with phase shifting transformers (PST). However, the operations of several PSTs deployed close to each other must be coordinated for them to be effective and to avoid their harmful interactions. Coordination of a group of such devices leads to a problem of multidimensional optimisation. This paper presents a method of optimal PST setting based on the particle swarm optimisation (PSO) algorithm. As an optimisation criterion the minimization of unscheduled flow through the given system has been applied. The impact of the number of particles in the swarm and their maximum permissible velocity on the optimisation algorithm’s efficiency was analysed. Results are presented for a 118-node test grid.
W odpowiedzi na rosnący problem przepływów nieplanowych coraz większa liczba operatorów systemów przesyłowych w Europie wyposaża swoje systemy w przesuwniki fazowe (PST). Jednakże użycie kilku PST zainstalowanych geograficznie lub elektrycznie blisko siebie musi być skoordynowane w celu skutecznego wykorzystania tych urządzeń i uniknięcia ich niekorzystnych interakcji. Koordynacja grupy takich urządzeń prowadzi do problemu optymalizacji wielowymiarowej. W artykule przedstawiono metodę optymalizacji nastaw PST opartą na algorytmie roju cząstek (PSO). Jako kryterium optymalizacji zastosowano minimalizację przepływu nieplanowego przez dany system. Przeanalizowano wpływ liczby cząstek roju oraz ich maksymalnej dozwolonej prędkości na efektywność algorytmu optymalizacji. Przedstawiono wyniki dla sieci testowej zawierającej 118 węzłów.
Źródło:
Acta Energetica; 2017, 3; 97-103
2300-3022
Pojawia się w:
Acta Energetica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Feature selection using particle swarm optimization in text categorization
Autorzy:
Aghdam, M. H.
Heidari, S.
Powiązania:
https://bibliotekanauki.pl/articles/91792.pdf
Data publikacji:
2015
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
classification system
feature selection
text categorization
particle swarm optimization (PSO)
system klasyfikacji
wybór funkcji
kategoryzacja tekstu
optymalizacja rojem cząstek
Opis:
Feature selection is the main step in classification systems, a procedure that selects a subset from original features. Feature selection is one of major challenges in text categorization. The high dimensionality of feature space increases the complexity of text categorization process, because it plays a key role in this process. This paper presents a novel feature selection method based on particle swarm optimization to improve the performance of text categorization. Particle swarm optimization inspired by social behavior of fish schooling or bird flocking. The complexity of the proposed method is very low due to application of a simple classifier. The performance of the proposed method is compared with performance of other methods on the Reuters-21578 data set. Experimental results display the superiority of the proposed method.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2015, 5, 4; 231-238
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Smart control of energy storage system in residential photovoltaic systems for economic and technical efficiency
Autorzy:
Kaczorowska, Dominika
Rezmer, Jacek
Janik, Przemysław
Sikorski, Tomasz
Powiązania:
https://bibliotekanauki.pl/articles/2202548.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
economic efficiency
energy storage system ESS
microgrid management
optimal power flow
OPF
particle swarm optimisation PSO
Opis:
In recent years, due to the increasing number of renewable energy sources, which are characterised by the stochastic nature of the generated power, interest in energy storage has increased. Commercial installations use simple deterministic methods with low economic efficiency. Hence, there is a need for intelligent algorithms that combine technical and economic aspects. Methods based on computational intelligence (CI) could be a solution. The paper presents an algorithm for optimising power flow in microgrids by using computational intelligence methods. This approach ensures technical and economic efficiency by combining multiple aspects in a single objective function with minimal numerical complexity. It is scalable to any industrial or residential microgrid system. The method uses load and generation forecasts at any time horizon and resolution and the actual specifications of the energy storage systems, ensuring that technological constraints are maintained. The paper presents selected calculation results for a typical residential microgrid supplied with a photovoltaic system. The results of the proposed algorithm are compared with the outcomes provided by a deterministic management system. The computational intelligence method allows the objective function to be adjusted to find the optimal balance of economic and technical effects. Initially, the authors tested the invented algorithm for technical effects, minimising the power exchanged with the distribution system. The application of the algorithm resulted in financial losses, €12.78 for the deterministic algorithm and €8.68 for the algorithm using computational intelligence. Thus, in the next step, a control favouring economic goals was checked using the CI algorithm. The case where charging the storage system from the grid was disabled resulted in a financial benefit of €10.02, whereas when the storage system was allowed to charge from the grid, €437.69. Despite the financial benefits, the application of the algorithm resulted in up to 1560 discharge cycles. Thus, a new unconventional case was considered in which technical and economic objectives were combined, leading to an optimum benefit of €255.17 with 560 discharge cycles per year. Further research of the algorithm will focus on the development of a fitness function coupled to the power system model.
Źródło:
Archives of Electrical Engineering; 2023, 72, 1; 81--102
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
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