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Wyświetlanie 1-15 z 21
Tytuł:
Vibroacoustic Real Time Fuel Classification in Diesel Engine
Autorzy:
Bąkowski, A.
Kekez, M.
Radziszewski, L.
Sapietova, A.
Powiązania:
https://bibliotekanauki.pl/articles/177686.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
fuel recognition
classification trees
particle swarm optimization (PSO)
random forest
Opis:
Five models and methodology are discussed in this paper for constructing classifiers capable of recognizing in real time the type of fuel injected into a diesel engine cylinder to accuracy acceptable in practical technical applications. Experimental research was carried out on the dynamic engine test facility. The signal of in-cylinder and in-injection line pressure in an internal combustion engine powered by mineral fuel, biodiesel or blends of these two fuel types was evaluated using the vibro-acoustic method. Computational intelligence methods such as classification trees, particle swarm optimization and random forest were applied.
Źródło:
Archives of Acoustics; 2018, 43, 3; 385-395
0137-5075
Pojawia się w:
Archives of Acoustics
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:
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:
A hybrid PSO approach for solving non-convex optimization problems
Autorzy:
Ganesan, T.
Vasant, P.
Elamvazuthy, I.
Powiązania:
https://bibliotekanauki.pl/articles/229756.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Kuhn-Tucker conditions (KT)
non-convex optimization
particle swarm optimization (PSO)
semi-classical particle swarm optimization (SPSO)
Opis:
The aim of this paper is to propose an improved particle swarm optimization (PSO) procedure for non-convex optimization problems. This approach embeds classical methods which are the Kuhn-Tucker (KT) conditions and the Hessian matrix into the fitness function. This generates a semi-classical PSO algorithm (SPSO). The classical component improves the PSO method in terms of its capacity to search for optimal solutions in non-convex scenarios. In this work, the development and the testing of the refined the SPSO algorithm was carried out. The SPSO algorithm was tested against two engineering design problems which were; ‘optimization of the design of a pressure vessel’ (P1) and the ‘optimization of the design of a tension/compression spring’ (P2). The computational performance of the SPSO algorithm was then compared against the modified particle swarm optimization (PSO) algorithm of previous work on the same engineering problems. Comparative studies and analysis were then carried out based on the optimized results. It was observed that the SPSO provides a better minimum with a higher quality constraint satisfaction as compared to the PSO approach in the previous work.
Źródło:
Archives of Control Sciences; 2012, 22, 1; 87-105
1230-2384
Pojawia się w:
Archives of Control Sciences
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:
Economic dispatch in power system networks including renewable energy resources using various optimization techniques
Autorzy:
Hafiz, Abrar Mohamed
Abdelrahman, M. Ezzat
Temraz, Hesham
Powiązania:
https://bibliotekanauki.pl/articles/1841222.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Economic Dispatch (ED)
Particle Swarm Optimization (PSO)
Sine-Cosine
Algorithm (SCA)
Photovoltaic (PV)
Opis:
Economic dispatch (ED) is an essential part of any power system network. ED is how to schedule the real power outputs from the available generators to get the minimum cost while satisfying all constraints of the network. Moreover, it may be explained as allocating generation among the committed units with the most effective minimum way in accordance with all constraints of the system. There are many traditional methods for solving ED, e.g., Newton-Raphson method Lambda-Iterative technique, Gaussian-Seidel method, etc. All these traditional methods need the generators’ incremental fuel cost curves to be increasing linearly. But practically the input-output characteristics of a generator are highly non-linear. This causes a challenging non-convex optimization problem. Recent techniques like genetic algorithms, artificial intelligence, dynamic programming and particle swarm optimization solve nonconvex optimization problems in a powerful way and obtain a rapid and near global optimum solution. In addition, renewable energy resources as wind and solar are a promising option due to the environmental concerns as the fossil fuels reserves are being consumed and fuel price increases rapidly and emissions are getting higher. Therefore, the world tends to replace the old power stations into renewable ones or hybrid stations. In this paper, it is attempted to enhance the operation of electrical power system networks via economic dispatch. An ED problem is solved using various techniques, e.g., Particle Swarm Optimization (PSO) technique and Sine-Cosine Algorithm (SCA). Afterwards, the results are compared. Moreover, case studies are executed using a photovoltaic-based distributed generator with constant penetration level on the IEEE 14 bus system and results are observed. All the analyses are performed on MATLAB software.
Źródło:
Archives of Electrical Engineering; 2021, 70, 3; 643-655
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new technique to design planar dipole antennas by using Bezier curve and Particle Swarm Optimization
Autorzy:
Homsup, N.
Silabut, W.
Kesornpatumanum, V.
Boonek, P.
Kuhirun, W.
Powiązania:
https://bibliotekanauki.pl/articles/140461.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
planar dipole antenna
Bézier curve
particle swarm optimization (PSO)
small antenna
dual band antenna
Opis:
This research presents a new technique which includes the principle of a Bezier curve and Particle Swarm Optimization (PSO) together, in order to design the planar dipole antenna for the two different targets. This technique can improve the characteristics of the antennas by modifying copper textures on the antennas with a Bezier curve. However, the time to process an algorithm will be increased due to the expansion of the solution space in optimization process. So as to solve this problem, the suitable initial parameters need to be set. Therefore this research initialized parameters with reference antenna parameters (a reference antenna operates on 2.4 GHz for IEEE 802.11 b/g/n WLAN standards) which resulted in the proposed designs, rapidly converted into the goals. The goal of the first design is to reduce the size of the antenna. As a result, the first antenna is reduced in the substrate size from areas of 5850 mm2 to 2987 mm2 (48.93% approximately) and can also operates at 2.4 GHz (2.37 GHz to 2.51 GHz). The antenna with dual band application is presented in the second design. The second antenna is operated at 2.4 GHz (2.40 GHz to 2.49 GHz) and 5 GHz (5.10 GHz to 5.45 GHz) for IEEE 802.11 a/b/g/n WLAN standards.
Źródło:
Archives of Electrical Engineering; 2016, 65, 3; 513-525
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
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:
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:
Fuzzy ranking based non-dominated sorting genetic algorithm-II for network overload alleviation
Autorzy:
Pandiarajan, K.
Babulal, C. K.
Powiązania:
https://bibliotekanauki.pl/articles/141059.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
non-dominated sorting genetic algorithm
generation rescheduling
particle swarm optimization (PSO)
differential evolution
overload index
Opis:
This paper presents an effective method of network overload management in power systems. The three competing objectives 1) generation cost 2) transmission line overload and 3) real power loss are optimized to provide pareto-optimal solutions. A fuzzy ranking based non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve this complex nonlinear optimization problem. The minimization of competing objectives is done by generation rescheduling. Fuzzy ranking method is employed to extract the best compromise solution out of the available non-dominated solutions depending upon its highest rank. N-1 contingency analysis is carried out to identify the most severe lines and those lines are selected for outage. The effectiveness of the proposed approach is demonstrated for different contingency cases in IEEE 30 and IEEE 118 bus systems with smooth cost functions and their results are compared with other single objective evolutionary algorithms like Particle swarm optimization (PSO) and Differential evolution (DE). Simulation results show the effectiveness of the proposed approach to generate well distributed pareto-optimal non-dominated solutions of multi-objective problem
Źródło:
Archives of Electrical Engineering; 2014, 63, 3; 367-384
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cellular particle swarm optimization with a simple adaptive local search strategy for the permutation flow shop scheduling problem
Autorzy:
Seck-Tuoh-Mora, Juan C.
Medina-Marin, Joselito
Martinez-Gomez, Erick S.
Hernandez-Gress, Eva S.
Hernandez-Romero, Norberto
Volpi-Leon, Valeria
Powiązania:
https://bibliotekanauki.pl/articles/230060.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
flow shop
particle swarm optimization (PSO)
local search strategy
hybrid search method
cellular automata
scheduling
Opis:
Permutation flow shop scheduling problem deals with the production planning of a number of jobs processed by a set of machines in the same order. Several metaheuristics have been proposed for minimizing the makespan of this problem. Taking as basis the previous Alternate Two-Phase PSO (ATPPSO) method and the neighborhood concepts of the Cellular PSO algorithm proposed for continuous problems, this paper proposes the improvement of ATPPSO with a simple adaptive local search strategy (called CAPSO-SALS) to enhance its performance. CAPSO-SALS keeps the simplicity of ATPPSO and boosts the local search based on a neighborhood for every solution. Neighbors are produced by interchanges or insertions of jobs which are selected by a linear roulette scheme depending of the makespan of the best personal positions. The performance of CAPSO-SALS is evaluated using the 12 different sets of Taillard’s benchmark problems and then is contrasted with the original and another previous enhancement of the ATPPSO algorithm. Finally, CAPSO-SALS is compared as well with other ten classic and state-of-art metaheuristics, obtaining satisfactory results.
Źródło:
Archives of Control Sciences; 2019, 29, 2; 205-226
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybrid method for the optimal reactive power dispatch and the control of voltagesin an electrical energy network
Autorzy:
Benchabira, Aissa
Khiat, Mounir
Powiązania:
https://bibliotekanauki.pl/articles/140740.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
electrical energy network
interior point method (IPM)
optimal reactive power dispatch (ORPD)
particle swarm optimization (PSO)
Opis:
This paper presents the resolution of the optimal reactive power dispatch (ORPD) problem and the control of voltages in an electrical energy system by using a hybrid algorithm based on the particle swarmoptimization (PSO) method and interior point method (IPM). The IPM is based on the logarithmic barrier (LB-IPM) technique while respecting the non-linear equality and inequality constraints. The particle swarmoptimization-logarithmic barrier-interior point method (PSO-LB-IPM) is used to adjust the control variables, namely the reactive powers, the generator voltages and the load controllers of the transformers, in order to ensure convergence towards a better solution with the probability of reaching the global optimum. The proposed method was first tested and validated on a two-variable mathematical function using MATLAB as a calculation and execution tool, and then it is applied to the ORPD problem to minimize the total active losses in an electrical energy network. To validate the method a testwas carried out on the IEEE electrical energy network of 57 buses.
Źródło:
Archives of Electrical Engineering; 2019, 68, 3; 535-551
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evaluation of the Shunt Active Power Filter apparent power ratio using particle swarm optimization
Autorzy:
Kouzou, A.
Mahmoudi, M. O.
Boucherit, M. S.
Powiązania:
https://bibliotekanauki.pl/articles/229885.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
effective apparent power
shunt active power filter
particle swarm optimization (PSO)
harmonics
unbalanced voltages
unbalanced load
Opis:
The main objective of this present paper is the study of the Shunt Active Power Filter (APF) compensations capability for different perturbations in AC power system such as current unbalance, phase shift current and undesired harmonics generated by nonlinear load and/or by the power system voltage. This capability is determined by the maximum rate of the apparent power that can be delivered. This study is based on the definition of the effective apparent power as defined in IEEE 1459-2000 which was proved to be the suitable amount to be concerned in the design process of different devices.
Źródło:
Archives of Control Sciences; 2010, 20, 1; 47-76
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Traffic fatalities prediction based on support vector machine
Autorzy:
Li, T.
Yang, Y.
Wang, Y.
Chen, C.
Yao, J.
Powiązania:
https://bibliotekanauki.pl/articles/223743.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
traffic accident
support vector machine
SVM
particle swarm optimization (PSO)
PSO
prediction model
optimal parameters
wypadek drogowy
Particle Swarm Optimization
model prognostyczny
optymalne parametry
Opis:
To effectively predict traffic fatalities and promote the friendly development of transportation, a prediction model of traffic fatalities is established based on support vector machine (SVM). As the prediction accuracy of SVM largely depends on the selection of parameters, Particle Swarm Optimization (PSO) is introduced to find the optimal parameters. In this paper, small sample and nonlinear data are used to predict fatalities of traffic accident. Traffic accident statistics data of China from 1981 to 2012 are chosen as experimental data. The input variables for predicting accident are highway mileage, vehicle number and population size while the output variables are traffic fatality. To verify the validity of the proposed prediction method, the back-propagation neural network (BPNN) prediction model and SVM prediction model are also used to predict the traffic fatalities. The results show that compared with BPNN prediction model and SVM model, the prediction model of traffic fatalities based on PSO-SVM has higher prediction precision and smaller errors. The model can be more effective to forecast the traffic fatalities. And the method using particle swarm optimization algorithm for parameter optimization of SVM is feasible and effective. In addition, this method avoids overcomes the problem of “over learning” in neural network training progress.
Źródło:
Archives of Transport; 2016, 39, 3; 21-30
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
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