Our interior point method includes an efficient implementation of a novel approach to constraint softening, which has only been tested in high-level languages before. We propose a modular software design that allows for high solver customization, while still producing compact and fast code. This work deals with the implementation of an interior point algorithm for use in embedded MPC applications. As a result, the use of model predictive controllers in these application domains remains challenging. In many cases, these applications also need to be implemented on embedded hardware with limited resources. Several emerging applications require the use of short sampling times to cope with the fast dynamics of the underlying process. Model predictive control (MPC) is an advanced control technique that requires solving an optimization problem at each sampling instant.
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