ADMM for MPC with state and input constraints, and input nonlinearity
In this paper we propose an Alternating Direction Method of Multipliers (ADMM) algorithm for solving a Model Predictive Control (MPC) optimization problem, in which the system has state and input constraints and a nonlinear input map. The resulting optimization is nonconvex, and we provide a proof o...
Main Authors: | East, S, Cannon, M |
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格式: | Conference item |
出版: |
Institute of Electrical and Electronics Engineers
2018
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