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1
Published in 2020 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2020.12.636
Abstract: Abstract Most of the existing stochastic model predictive control (SMPC) algorithms for systems subject to random disturbance are designed offline using the distribution information of the uncertainties. In this paper, we propose an iterative learning…
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Keywords:
iterative learning;
adaptive constraint;
learning stochastic;
constraint tightening ... See more keywords
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2
Published in 2023 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2022.3231555
Abstract: Limited computation resources forces early (sub-optimal) termination of the solvers used for model predictive controllers (MPCs). This can compromise the feasibility and stability guarantees of the initial MPC design. In this letter, we consider a…
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Keywords:
sub optimal;
optimal mpc;
constraint tightening;
dynamic constraint ... See more keywords