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Title:Razvoj naprednega adaptivnega regulatorja za mehatronske sisteme
Authors:Fister, Dušan (Author)
Brezočnik, Miran (Mentor) More about this mentor... New window
Šafarič, Riko (Mentor) More about this mentor... New window
Files:.pdf MAG_Fister_Dusan_2017.pdf (2,36 MB)
MD5: CFCBF3C573DEEFE52CD2E7E860DC2FB1
 
Language:Slovenian
Work type:Master's thesis/paper (mb22)
Typology:2.09 - Master's Thesis
Organization:FS - Faculty of Mechanical Engineering
Abstract:V magistrski nalogi predstavljamo, opisujemo ter razlagamo princip delovanja nelinearnega naprednega adaptivnega hitrostnega regulatorja, ki smo ga izdelali za potrebe napredne regulacije na enoosnem robotu. Tega krmilimo z algoritmom evolucijskih strategij, ki je sposoben dinamičnega iskanja rešitev, kjer se vrednost funkcije uspešnosti spreminja s časom. Pri tem smo vrednost funkcije uspešnosti napovedovali s pomočjo nevronske mreže (angl. Artificial Neural Network, krajše ANN). Predlagano metodo smo testirali na realnem laboratorijskem robotskem sistemu z eno stopnjo prostosti (angl. one degree of freedom, krajše 1 D.O.F.) in ugotovili, da je primeren za regulacijo v realnem času (odzivni čas 1-5 ms). Izvedena je bila primerjava z linearnim PI-hitrostnim regulatorjem, rezultati pa so pokazali uspešnejše delovanje nelinearnega hitrostnega regulatorja.
Keywords:online-regulacija, identifikacija, evalvacija, optimizacija, realni čas
Year of publishing:2017
Publisher:[D. Fister]
Source:Maribor
UDC:681.52(043.2)
COBISS_ID:21180438 New window
NUK URN:URN:SI:UM:DK:PBRBBOH8
Views:616
Downloads:125
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:KTFMB - FS
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:07.08.2017

Secondary language

Language:English
Title:Development of advanced adaptive controller for mechatronic systems
Abstract:In this M.Sc. Thesis, a non-linear advanced adaptive controller is proposed and described, which was used for the purpose of velocity control on a single degree of freedom robotic mechanism. The controller is based on the algorithm of dynamic evolution strategy, which is capable of searching the global optimum dynamically, i.e. when the fitness function is changing through time. The fitness function calculation has been done by implementing an artificial neural network, which was simulating the behavior of the real system. We tested the proposed algorithm on the robotic mechanism and compared the results to the PI-velocity controller. We concluded, that the proposed approach of identification and optimization is appropriate for online real-time control (response time 1-5 ms). Furthermore, non-linear controller outperformed the linear controller, according to conducted tests.
Keywords:online control, identification, evaluation, optimization, real-time


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