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Digital
Library of the European Council for Modelling and Simulation |
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Title: |
Continuous-Time
Vs. Discrete-Time Identification Models Used For Adaptive Control Of
Nonlinear Process |
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Authors: |
Jiri
Vojtesek, Petr Dostal |
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Published in:
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(2016).ECMS 2016 Proceedings edited
by: Thorsen Claus, Frank Herrmann, Michael Manitz, Oliver Rose, European Council for Modeling and
Simulation. doi:10.7148/2016 ISBN:
978-0-9932440-2-5 30th
European Conference on Modelling and Simulation, Regensburg Germany, May 31st
– June 3rd, 2016 |
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Citation
format: |
Jiri
Vojtesek, Petr Dostal (2016). Continuous-Time Vs. Discrete-Time
Identification Models Used For Adaptive Control Of Nonlinear Process, ECMS
2016 Proceedings edited by: Thorsten Claus, Frank Herrmann, Michael Manitz, Oliver Rose European Council for Modeling
and Simulation. doi:10.7148/2016-0320 |
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DOI: |
http://dx.doi.org/10.7148/2016-0320 |
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Abstract: |
An adaptive control is a technique
where the controller adopts a structure or parameters somehow to the control conditions
and the state of the controlled system. One way how we can fulfil the adaptivity of the
controller is a recursive identification of the controlled system
which satisfies that parameters of the controller changes according to
parameters of the controlled system during the whole control process. The
goal of this contribution is to compare identification models that work in continuous
and discrete time. The control synthesis uses polynomial approach that
satisfies basic control requirements such as a stability,
a disturbance attenuation and a reference signal tracking. The control response
could be tuned by the choice of the root position in the Pole-placement
method. Moreover, this control method could be easily programmable that is
big advantage while we use this method in simulation software such as Matlab etc. |
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