Temat: Particle Swarm Optimization - Katalog OPAC zbiorów

Skocz do pozycji: 1.

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

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Skocz do pozycji: 2.

Tytuł:: Particle swarm optimization for tuning PSS-PID controller of synchronous generator
Autorzy:: Derrar, A.
Naceri, A.
Powiązania:: https://bibliotekanauki.pl/articles/384775.pdf
Data publikacji:: 2017
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: synchronous generator
PSS
particle swarm optimization (PSO)
PID controller
Opis:: In this paper the design an optimal PSS-PID controller for single machine connected to an infinite bus (SMIB). We presented a novel application of particle swarm optimization (PSO) for the optimal tuning of the new PSS-PID controller. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The synchronous generator is modeled and the PSO algorithm is implemented in Simulink of Matlab. The obtained results have proved that (PSO) are a powerful tools for optimizing the PSS parameters, and more robustness of the system IEEE SMIB.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2017, 11, 1; 48-52
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

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

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Skocz do pozycji: 4.

Tytuł:: On the efficiency of population-based optimization in finding best parameters for RGB-D visual odometry
Autorzy:: Kostusiak, Aleksander
Skrzypczyński, Piotr
Powiązania:: https://bibliotekanauki.pl/articles/384397.pdf
Data publikacji:: 2019
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: particle swarm optimization (PSO)
evolutionary algorithm
visual odometry
RGB-D
Opis:: Visual odometry estimates the transformations between consecutive frames of a video stream in order to recover the camera’s trajectory. As this approach does not require to build a map of the observed environment, it is fast and simple to implement. In the last decade RGBD cameras proliferated in roboTIcs, being also the sensors of choice for many practical visual odometry systems. Although RGB-D cameras provide readily available depth images, that greatly simplify the frame-to-frame transformations computaTIon, the number of numerical parameters that have to be set properly in a visual odometry system to obtain an accurate trajectory estimate remains high. Whereas seƫng them by hand is certainly possible, it is a tedious try-and-error task. Therefore, in this article we make an assessment of two population-based approaches to parameter opTImizaTIon, that are for long time applied in various areas of robotics, as means to find best parameters of a simple RGB-D visual odometry system. The optimization algorithms investigated here are particle swarm optimization and an evolutionary algorithm variant. We focus on the optimization methods themselves, rather than on the visual odometry algorithm, seeking an efficient procedure to find parameters that minimize the estimated trajectory errors. From the experimental results we draw conclusions as to both the efficiency of the optimization methods, and the role of particular parameters in the visual odometry system.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2019, 13, 2; 5-14
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Increased Performance of a Hybrid Optimizer for Simulation Based Controller Parameterization
Autorzy:: Neugebauer, R.
Hipp, K.
Hellmich, A.
Schlegel, H.
Powiązania:: https://bibliotekanauki.pl/articles/384707.pdf
Data publikacji:: 2012
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: controller parameterization
simulation based optimization
particle swarm optimization (PSO)
Nelder-Mead
Opis:: The controller parameterization is often carried out by applying basic empirical formulas within an integrated automatic design. Hence, the determined settings are often insufficiently verified by the resulting system behavior. In this paper an approach for the controller parameterization by using methods of simulation based optimization is presented. This enables the user to define specific restrictions e.g. the complementary sensitivity function (CSF) to influence the dynamic behavior of the control loop. Furthermore it is possible to choose alternative optimization criteria. A main influence factor for practical offline as well as controller internal optimization methods is the execution time, which can be reduced by applying a hybrid optimization strategy. Thus, the paper presents a performance comparison between the straight global Particle-Swarm-Optimization (PSO) algorithm and the combination of the global PSO with the local optimization algorithm of Nelder-Mead (NM) to a hybrid optimizer (HO) based on examples.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2012, 6, 1; 42-45
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: A Comparative Study of PID Controller Tuning Using GA, EP, PSO and ACO
Autorzy:: Nagaraj, B.
Vijayakumar, P.
Powiązania:: https://bibliotekanauki.pl/articles/384767.pdf
Data publikacji:: 2011
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: ant colony algorithm
evolutionary program
genetic algorithm particle swarm optimization and soft computing
Opis:: Proportional - Integral - Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. How ever PID controller are poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This article comes up with a hybrid approach involving Genetic Algorithm (GA), Evolutionary Pro gramming (EP), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). The proposed hybrid algorithm is used to tune the PID parameters and its per formance has been compared with the conventional me thods like Ziegler Nichols and Cohen Coon method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. Speed control of DC motor process is used to assess the efficacy of the heuristic algorithm methodology
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2011, 5, 2; 42-48
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Control imrovement of shunt active power filter using an optimized-PI controller based on ant colony algorithm and swarm optimization
Autorzy:: Berbaoui, B.
Ferdi, B.
Benachaiba, C.
Dehini, R.
Powiązania:: https://bibliotekanauki.pl/articles/385137.pdf
Data publikacji:: 2010
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: ant colony optimization
particle swarm optimization (PSO)
shunt active power filter
armonic compensation
PI controller
Opis:: In the last years, there has been a increase currents harmonics on electrical network injected by nonlinear loads, such as rectifier equipment used in telecommunication system, power suppliers, domestic appliances, ect. This paper makes a comparison of the effectiveness of the two methods on particular optimization problem, namely. The tuning of the parameters for PI DC link voltage to a shunt active power filter. The simulation results demonstrates that the optimized PI controller by ant colony (ACO) presents a advantage of little response time and best control performances compared to the optimized PI with Particle swarm (PSO). This comparison is shown on redu cing harmonic current supply (THD).
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 4; 19-25
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Comparative Study of Optimised Artificial Intelligence Based First Order Sliding Mode Controllers for Position Control of a DC Motor Actuator
Autorzy:: Nyong-Bassey, B. E.
Akinloye, B.
Powiązania:: https://bibliotekanauki.pl/articles/385114.pdf
Data publikacji:: 2016
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: adaptive fuzzy control
DC motor position control
genetic algorithm
particle swarm optimization (PSO)
sliding mode control
Opis:: This paper aims at critically reviewing various sliding mode control measures applied to Permanent Magnet DC Motor actuator for position control. At first, a hybrid sliding mode controller was examined with its advantages and disadvantages. Then, the smooth sliding mode controller in the same manner. The shortcomings of the two methods were overcome by proper switch design and also using tanh-sinh hyperbolic function. The sliding mode controller switches on when either disturbance or noise is detected. Genetic Algorithm Computational tuning technique is employed to optimize the gains of the controllers for optimal response.The performance of the proposed controller architecture, as well as the reviewed controllers, have been compared for performance evaluation with respect to several operating conditions. This includes load torque disturbance injection, noise injection in a feedback loop, motor nonlinearity exhibited by parameters variation, and a step change in reference input demand.
Źródło:: Journal of Automation Mobile Robotics and Intelligent Systems; 2016, 10, 3; 58-71
1897-8649
2080-2145
Pojawia się w:: Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Algorytmy stadne w problemach optymalizacji
Swarm Algorithms in Optimization Problems
Autorzy:: Filipowicz, B.
Kwiecień, J.
Powiązania:: https://bibliotekanauki.pl/articles/274567.pdf
Data publikacji:: 2011
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: optymalizacja nieliniowa
algorytm PSO
algorytm pszczeli
algorytm świetlika
nonlinear optimization
particle swarm optimization (PSO)
bee algorithm
firefly algorithm
Opis:: W artykule przedstawiono zastosowanie algorytmu optymalizacji rojem cząstek, algorytmu pszczelego i algorytmu świetlika do wyznaczenia optymalnego rozwiązania wybranych testowych funkcji ciągłych. Przedstawiono i porównano wyniki badań dla funkcji Rosenbrocka, Rastrigina i de Jonga.
This paper presents particle swarm optimization, bee algorithm and firefly algorithm, used for optimal solution of selected continuous well-known functions. Results of these algorithms are compared to each other on Rosenbrock, Rastrigin and de Jong functions.
Źródło:: Pomiary Automatyka Robotyka; 2011, 15, 12; 152-157
1427-9126
Pojawia się w:: Pomiary Automatyka Robotyka
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Mobile Robot Path Planning with Obstacle Avoidance using Particle Swarm Optimization
Planowanie bezkolizyjnej ścieżki ruchu robota mobilnego przy użyciu algorytmu rojowego
Autorzy:: Chołodowicz, E.
Figurowski, D.
Powiązania:: https://bibliotekanauki.pl/articles/274869.pdf
Data publikacji:: 2017
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:: mobile robot
path planning
obstacle avoidance
particle swarm optimization (PSO)
dynamic environment
robot mobilny
planowanie ścieżki ruchu
unikanie przeszkód
algorytm rojowy
dynamiczne środowisko
Opis:: This paper presents a constrained Particle Swarm Optimization (PSO) algorithm for mobile robot path planning with obstacle avoidance. The optimization problem is analyzed in static and dynamic environments. A smooth path based on cubic splines is generated by the interpolation of optimization solution; the fitness function takes into consideration the path length and obstaclegenerated repulsive zones. World data transformation is introduced to reduce the optimization algorithm computational complexity. Different scenarios are used to test the algorithm in simulation and real-world experiments. In the latter case, a virtual robot following concept is exploited as part of the control strategy. The path generated by the algorithm is presented in results along with its execution by the mobile robot.
W artykule przedstawiono algorytm rojowy z ograniczeniami realizujący planowanie bezkolizyjnej ścieżki ruchu robota mobilnego. Problem optymalizacyjny został przeanalizowany dla środowiska statycznego i dynamicznego. Do stworzenia gładkiej ścieżki ruchu wykorzystano interpolację rozwiązania optymalizacji przy użyciu sześciennych funkcji sklejanych. Funkcja kosztu uwzględnia długość ścieżki ruchu oraz penalizację za naruszenie przestrzeni przeszkód. Wprowadzono transformację świata w celu redukcji złożoności obliczeniowej algorytmu optymalizacji. Przeprowadzono zróżnicowane scenariusze badawcze testujące algorytm w eksperymentach symulacyjnych i rzeczywistych. W przypadku tych ostatnich wykorzystano ideę podążania za wirtualnym robotem. Zaprezentowano wyniki obrazujące wygenerowaną ścieżkę ruchu oraz ocenę jej realizacji przez robota mobilnego.
Źródło:: Pomiary Automatyka Robotyka; 2017, 21, 3; 59-68
1427-9126
Pojawia się w:: Pomiary Automatyka Robotyka
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 11.

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

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