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Constrained MPC to track time‐varying reference signals: Online optimization of virtual reference signals and controller states
Author(s) -
Wada Nobutaka,
Tsurushima Seiya
Publication year - 2016
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22337
Subject(s) - control theory (sociology) , integrator , linear matrix inequality , offset (computer science) , controller (irrigation) , convex optimization , computer science , model predictive control , optimization problem , track (disk drive) , control engineering , mathematical optimization , engineering , control (management) , regular polygon , mathematics , algorithm , bandwidth (computing) , computer network , geometry , artificial intelligence , agronomy , biology , programming language , operating system
In this paper, we propose a model predictive control (MPC) algorithm for linear systems with constraints to track time‐varying reference signals. The proposed controller is assumed to have an integrator as a servo compensator. In the proposed control approach, the value of the integrator state is optimally initialized at each sampling time to improve tracking control performance until the cost function becomes sufficiently small. Moreover, while the cost function is sufficiently small, the integral action is used to achieve offset‐free tracking. The control algorithm is reduced to a convex optimization problem with linear matrix inequality constraints. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.