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- W2900794160 abstract "We propose a highly parallelizable Newton-type method for nonlinear model predictive control by exploiting the particular structure of the associated Karush-Kuhn-Tucker conditions. These equations are approximately decoupled into single step subproblems along the prediction horizon for parallelization. The coupling variable of each subproblem is approximated toward its optimal value by a simple but effective method in every iteration. The proposed algorithm is applied to control a quadrotor. The numerical simulation results show that the proposed algorithm is highly parallelizable and converges with only a few iterations even to a high accuracy. The proposed method is also shown to be faster compared with several state-of-the-art algorithms." @default.
- W2900794160 created "2018-11-29" @default.
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- W2900794160 date "2018-01-01" @default.
- W2900794160 modified "2023-10-05" @default.
- W2900794160 title "A Highly Parallelizable Newton-type Method for Nonlinear Model Predictive Control" @default.
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- W2900794160 doi "https://doi.org/10.1016/j.ifacol.2018.11.058" @default.
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