IMPACT: A Toolchain for Nonlinear Model Predictive Control Specification, Prototyping, and DeploymentWe present IMPACT, a flexible toolchain for nonlinear model predictive
control (NMPC) specification with automatic code generation capabilities. The
toolchain reduces the engineering complexity of NMPC implementations by
providing the user with an easy-to-use application programming interface, and
with the flexibility of using multiple state-of-the-art tools and numerical
optimization solvers for rapid prototyping of NMPC solutions. IMPACT is written
in Python, users can call it from Python and MATLAB, and the generated NMPC
solvers can be directly executed from C, Python, MATLAB and Simulink. An
application example is presented involving problem specification and deployment
on embedded hardware using Simulink, showing the effectiveness and
applicability of IMPACT for NMPC-based solutions.
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