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Title:Adaptivno vodenje osnovano na algoritmih računske inteligence
Authors:Šafarič, Jakob (Author)
Fister, Iztok (Mentor) More about this mentor... New window
Lovrec, Darko (Mentor) More about this mentor... New window
Bratina, Božidar (Co-mentor)
Files:.pdf MAG_Safaric_Jakob_2018.pdf (4,36 MB)
MD5: C8F53FD0CFC95E1498410C2CD799D7FE
 
.zip MAG_Safaric_Jakob_2018.zip (133,98 KB)
MD5: 816FFA9846A8E85BC6F420D99C04E0C6
 
Language:Slovenian
Work type:Master's thesis/paper (mb22)
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Na področju robotike obstaja ogromno nelinearnih sistemov, ki se še vedno vodijo z linearnimi regulatorji, čeprav ti niso optimalna rešitev za dani problem. V tem magistrskem delu je predstavljen hitrostni adaptivni nelinearni regulator, ki je sposoben voditi nelinearno progo boljše kot linearni regulatorji. Razviti regulator je sestavljen iz algoritma po vzorih iz narave, ki optimira vrednost referenčnega toka, in umetne nevronske mreže, ki je sposobna napovedati vrednost ocenitvene funkcije za izbrani algoritem. Pri tem primerjamo vpliv različnih algoritmov po vzorih iz narave na delovanje predlaganega regulatorja. V naši primerjalni analizi smo zajeli naslednje algoritme: evolucijsko strategijo, diferencialno evolucijo, optimizacijo z roji delcev in algoritmom po vzoru obnašanja netopirjev.
Keywords:nelinearni adaptivni regulator, umetne nevronske mreže, evolucijski algoritmi, algoritmi inteligence rojev
Year of publishing:2018
Publisher:J. Šafarič
Source:[Maribor
UDC:004.434:004.8(043.2)
COBISS_ID:21806102 New window
NUK URN:URN:SI:UM:DK:I1AQ0SEM
Views:814
Downloads:205
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Categories:KTFMB - FERI
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Licences

License:CC BY-NC-SA 4.0, Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Link:http://creativecommons.org/licenses/by-nc-sa/4.0/
Description:A Creative Commons license that bans commercial use and requires the user to release any modified works under this license.
Licensing start date:26.08.2018

Secondary language

Language:English
Title:Adaptive control based on computational intelligence
Abstract:In robotics, there are a lot of nonlinear systems, which are still controlled using linear controllers, even though they are not optimal solutions for the given problem. In this work, an adaptive nonlinear velocity controller is presented, which is better suited for control of nonlinear systems. The presented controller consists from nature inspired algorithm, which optimizes current reference, and artificial neural network, which is used for fitness function evaluation. A comparison of controller operation, when different nature inspired algorithms are used, is also presented in this work. Thus, the following nature inspired algorithms were captured in our comparison study: evolutionary strategy, differential evolution, particle swarm algorithm and bat algorithm.
Keywords:Nonlinear adaptive controller, Artificial neural networks, Evolution algorithms, Swarm intelligence algorithms


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