DocumentCode :
3743007
Title :
Reduced complexity control design for symmetric LPV systems
Author :
Claus Danielson;Stefano Di Cairano
Author_Institution :
Mitsubishi Electric Research Laboratories, Cambridge MA, United States of America
fYear :
2015
Firstpage :
72
Lastpage :
77
Abstract :
We use symmetry to reduce the computational complexity of designing parameter-dependent controllers and Lyapunov functions. We propose three complementary methods for exploiting symmetry to reduce the complexity. The first method uses symmetry to reduce the number of design variables. The second method uses symmetry to reduce the dimension of the design variables. And the third method reduces the number of linear matrix inequalities that the design variables must satisfy. We apply our reduced complexity control design to a building control problem. We show that, for this example, our method leads to an exponential decrease in the number of design variables and linear matrix inequalities.
Keywords :
"Lyapunov methods","Linear matrix inequalities","Linear systems","Orbits","Control systems","Stability analysis","Complexity theory"
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2015 IEEE 54th Annual Conference on
Type :
conf
DOI :
10.1109/CDC.2015.7402088
Filename :
7402088
Link To Document :
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