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1

Behaviour of unmanned aircraft in formation

Konatowski Stanisław, Tatko Sebastian

Przegląd Elektrotechniczny

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2023

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R. 99, nr 5

53--58

EN

For the described model of the dynamics of the unmanned aircraft, made in the Matlab/Simulink environment, an innovative method of controlling the UAV formation and the laws of dynamics governing the complex system were presented. The software implementation of the UAV model shows the process of building the system and selecting the settings of MPC, PID and LQR regulators. The proposed swarming algorithm is based on measuring mutual distances and bearings between individual aircraft. The correctness of the algorithm's operation was tested in a simulation manner with the use of a large list of characteristics. The article also includes an analysis of the influence of measurement uncertainty on the formation behaviour in flight.

PL

Dla opisanego modelu dynamiki bezzałogowego statku powietrznego, wykonanego w środowisku Matlab/Simulink, przedstawiona została nowatorska metoda sterowania formacją BSP oraz prawa dynamiki rządzące układem złożonym. Implementacja programowa modelu BSP ukazuje proces budowy układu oraz doboru nastaw regulatorów MPC, PID oraz LQR. Zaproponowany algorytm rojowy bazuje na pomiarze wzajemnych odległości oraz namiarów między poszczególnymi statkami powietrznymi. Poprawność działania algorytmu została sprawdzona w sposób symulacyjny z wykorzystaniem licznego zestawienia charakterystyk. Artykuł zawiera także analizę wpływu niepewności pomiarów na zachowanie formacji w locie.

2

Swarm intelligence integrated approach for experimental investigation in milling of multiwall carbon nanotube/polymer nanocomposites

Kharwar Prakhar Kumar, Verma Rajesh Kumar, Mandal Nirmal Kumar, Mondal Arpan Kumar

Archive of Mechanical Engineering

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2020

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LXVII, nr 3

353--376

EN

In manufacturing industries, the selection of machine parameters is a very complicated task in a time-bound manner. The process parameters play a primary role in confirming the quality, low cost of manufacturing, high productivity, and provide the source for sustainable machining. This paper explores the milling behavior of MWCNT/epoxy nanocomposites to attain the parametric conditions having lower surface roughness (Ra) and higher materials removal rate (MRR). Milling is considered as an indispensable process employed to acquire highly accurate and precise slots. Particle swarm optimization (PSO) is very trendy among the nature-stimulated metaheuristic method used for the optimization of varying constraints. This article uses the non-dominated PSO algorithm to optimize the milling parameters, namely, MWCNT weight% (Wt.), spindle speed (N), feed rate (F), and depth of cut (D). The first setting confirmatory test demonstrates the value of Ra and MRR that are found as 1.62 µm and 5.69 mm3/min, respectively and for the second set, the obtained values of Ra and MRR are 3.74 µm and 22.83 mm3/min respectively. The Pareto set allows the manufacturer to determine the optimal setting depending on their application need. The outcomes of the proposed algorithm offer new criteria to control the milling parameters for high efficiency.

3

Application of the Lennard-Jones potential in modelling robot motion

Wójcicki Piotr, Zientarski Tomasz

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2019

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T. 9, nr 4

14--17

EN

The article proposes a method of controlling the movement of a group of robots with a model used to describe the interatomic interactions. Molecular dynamics simulations were carried out in a system consisting of a moving groups of robots and fixed obstacles. Both the obstacles and the group of robots consisted of uniform spherical objects. Interactions between the objects are described using the Lennard-Jones potential. During the simulation, an ordered group of robots was released at a constant initial velocity towards the obstacles. The objects’ mutual behaviour was modelled only by changing the value of the interaction strength of the potential. The computer simulations showed that it is possible to find the optimal value of the potential impact parameters that enable the implementation of the assumed robotic behaviour scenarios. Three possible variants of behaviour were obtained: stopping, dispersing and avoiding an obstacle by a group of robots.

PL

W artykule zaproponowano metodę kontrolowania ruchu grupy robotów za pomocą modelu stosowanego do opisu oddziaływań międzyatomowych. Przeprowadzono symulacje metodą dynamiki molekularnej w układzie składającym się z ruchomych grup robotów oraz nieruchomych przeszkód. Zarówno przeszkody, jak i roboty składały się z jednolitych sferycznych obiektów. Oddziaływania między obiektami opisano za pomocą potencjału Lennard-Jonesa. Podczas symulacji, początkowo uporządkowana grupa robotów poruszała się ze stałą prędkością w kierunku przeszkód. Wzajemne zachowanie obiektów modelowano tylko poprzez zmianę wartości parametrów potencjału oddziaływań. Symulacje komputerowe wykazały, że możliwe jest znalezienie optymalnych wartości parametrów oddziaływania, które umożliwiają uzyskanie pożądanego zachowania robotów. W trakcie symulacji uzyskano trzy możliwe warianty zachowania: zatrzymywanie, rozpraszanie i omijanie przeszkód przez grupę robotów.

4

Metoda samoorganizacji i podążania za liderem roju nieholonomicznych robotów mobilnych z wykorzystaniem wirtualnych elementów sprężysto-tłumiących

Eremeyev V., Wiech J.

Przegląd Mechaniczny

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2018

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nr 5

28--33

PL

Celem pracy jest demonstracja metody samoorganizacji i podążania za liderem nieholonomicznego roju robotów mobilnych, opartej na wirtualnych, tłumionych, liniowych sprężynach łączących sąsiadujące roboty. Analizę metody sterowania poprzedza wyprowadzenie dynamiki dwukołowego robota oraz określenie zależności między wirtualnymi siłami a wejściami sterującymi robota w celu osiągnięcia stabilnej formacji roju. Analizowane są dwa przypadki sterowania rojem. W pierwszym przypadku spójność roju jest osiągnięta przez wirtualne sprężyny z tłumikami, łączące najbliższe roboty bez wyznaczonego lidera. W drugim przypadku wprowadzany jest lider roju oddziałujący wirtualnymi siłami na najbliższych i drugich sąsiadów, umożliwiając podążanie roju za liderem. Praca kończy się symulacjami numerycznymi oceniającymi wydajność zaproponowanej metody sterowania rojem.

EN

This paper presents a method for self-organization and leader following of nonholonomic robotic swarm based on virtual spring damper mesh. The dynamics of two wheel robot is derived using Euler-Lagrange’s method and relation between virtual forces and robot control inputs is defined in order to establish stable desired swarm formation. We analyze two cases of swarm control. In the first case the swarm cohesion is achieved without designated leader by virtual spring damper mesh connecting nearest neighboring robots. In the second case we introduce a swarm leader interacting with nearest and second neighbors allowing the swarm to follow the leader. Numeric simulation results are presented to illustrate the performance of the proposed control method.

5

Voice recognition through the use of Gabor transform and heuristic algorithm

Woźniak M., Połap D.

International Journal of Electronics and Telecommunications

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2017

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Vol. 63, No. 2

159--164

EN

Increasingly popular use of verification methods based on specific characteristics of people like eyeball, fingerprint or voice makes inventing more accurate and irrefutable methods of that urgent. In this work we present voice verification based on Gabor transformation. Proposed approach involves creation of spectrogram, which serves as a habitat for the population in selected heuristic algorithm. The use of heuristic allows for feature extraction to enable identity verification using classical neural network. The results of the research are presented and discussed to show efficiency of the proposed methodology.

6

Exit selection process during crowd evacuation, modelled on the cockroach emergent behaviour

Zajdel M., Filipowicz B.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2014

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Vol. 62, nr 3

557--563

EN

Groups of living creatures are often faced with searching for resources and choosing between one or more alternatives of resource site. Such a process is connected either with calm food acquirement or looking for a safe place to hide from danger. The question is, what kind of criteria are taken into consideration and what induces the collective decision, when all individuals in a swarm are equal. This paper identifies a simple mechanism of shelter selection by cockroach herd, whereby an emergent decision is made with limited information and without centralization of information processing or comparison of available solutions. The mechanism leads to the optimal benefit for both a group and an individual. The proposed model activates swarm self-organization and is independent of species, therefore, a possible application to human crowd control has been studied.

7

Reinforcement Learning with Approximation Spaces

Peters J.F., Henry Ch.

Fundamenta Informaticae

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2006

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Vol. 71, nr 2,3

323-349

EN

This paper introduces a rough set approach to reinforcement learning by swarms of cooperating agents. The problem considered in this paper is how to guide reinforcement learning based on knowledge of acceptable behavior patterns. This is made possible by considering behavior patterns of swarms in the context of approximation spaces. Rough set theory introduced by Zdzisaw Pawlak in the early 1980s provides a ground for deriving pattern-based rewards within approximation spaces. Both conventional and approximation space-based forms of reinforcement comparison and the actor-critic method as well as two forms of the off-policy Monte Carlo learning control method are investigated in this article. The study of swarm behavior by collections of biologically-inspired bots is carried out in the context of an artificial ecosystem testbed. This ecosystem has an ethological basis that makes it possible to observe and explain the behavior of biological organisms that carries over into the study of reinforcement learning by interacting robotic devices. The results of ecosystem experiments with six forms of reinforcement learning are given. The contribution of this article is the presentation of several viable alternatives to conventional reinforcement learning methods defined in the context of approximation spaces.