Implementation of soft-constrained MPC for Tracking using its semi-banded problem structure
arxiv(2024)
摘要
Model Predictive Control (MPC) is a popular control approach due to its
ability to consider constraints, including input and state restrictions, while
minimizing a cost function. However, in practice, said constraints can result
in feasibility issues, either because the system model is not accurate or due
to the existence of external disturbances. To mitigate this problem, a solution
adopted by the MPC community is the use of soft constraints. In this article,
we consider a not-so-typical methodology to encode soft constraints in a
particular MPC formulation known as MPC for Tracking (MPCT), which has several
advantages when compared to standard MPC formulations. The motivation behind
the proposed encoding is to maintain the semi-banded structure of the
ingredients of a recently proposed solver for the considered MPCT formulation,
thus providing an efficient and fast solver when compared to alternative
approaches from the literature. We show numerical results highlighting the
benefits of the formulation and the computational efficiency of the solver.
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