Design of an Adaptive Robust Controller Based on the Representation of a Quasi-linear Model in the Form of a Tensor Product
Author(s):
Alexander Alekseevich Shabashov
Postgraduate student of the Department of Applied Mathematics of the
Arzamas Polytechnic Institute (branch) of the Nizhny Novgorod State Technical University n. a. R.E. Alekseev (API NSTU),
1st category engineer of the JSC "Arzamas Research and Production Enterprise "TEMP-AVIA" (JSC ARPE "TEMP-AVIA")
aa.shabashov@mail.ru
Vladimir Vasilievich Pozdyaev
Doctor of Physical and Mathematical Sciences, Associate Professor, Associate Professor of the Department of Applied Mathematics of the
Arzamas Polytechnic Institute (branch) of the Nizhny Novgorod State Technical University n. a. R.E. Alekseev (API NSTU),
1st category engineer of the JSC "Arzamas Research and Production Enterprise "TEMP-AVIA" (JSC ARPE "TEMP-AVIA")
vpozdyaev+diffjournal@gmail.com
Artem Alekseevich Plotnikov
Master degree student of the Department of Applied Mathematics of the
Arzamas Polytechnic Institute (branch) of the Nizhny Novgorod State Technical University n. a. R.E. Alekseev (API NSTU),
engineer of the JSC "Arzamas Research and Production Enterprise "TEMP-AVIA" (JSC ARPE "TEMP-AVIA")
artyom152rus@yandex.ru
Abstract:
The problem of synthesizing an adaptive robust controller
using a tensor representation of a
quasi-linear parameter-varying model is considered.
This type of approximation of nonlinear dynamical systems
can be reduced to convex polytopic forms in over a given parameter range.
As a result, convex programming methods are applicable to them,
including formulation of the problem in terms of linear matrix inequalities.
The theory of H-infinity-optimal control is used as a
technique for the synthesis of robust controllers.
The result of the synthesis is a tensor model
that describes a family of robust controllers
that ensure stability and controllability of the object
for the entire range of varied parameters.
Keywords
- adaptive controllers
- linear matrix inequalities
- quasi-linear parameter-varying model
- robust controllers
- tensor product
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