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Low latency output feedback predictive control based on optimality conditions
Author(s) -
Kögel Markus,
Findeisen Rolf
Publication year - 2018
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201800429
Subject(s) - parameterized complexity , control theory (sociology) , model predictive control , optimization problem , observer (physics) , computer science , latency (audio) , optimal control , feedback control , controller (irrigation) , control (management) , mathematical optimization , mathematics , control engineering , algorithm , engineering , artificial intelligence , telecommunications , agronomy , physics , quantum mechanics , biology
In output feedback predictive control the control input is calculated by solving an optimization problem at each time instant based on a state estimate obtained by an observer. To efficiently counteract disturbances it is important to reduce the delay/latency due to the solution of the optimization problem. To this end we present an approach splitting the optimization into two phases: In the inter‐sample period a set of control laws parameterized by future measurements is determined exploiting the optimality conditions. Once the new measurement is available, the controller selects the corresponding control law and determines the optimal input, which can be achieved fast and with a low computational demand.