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Releases: Eric-Bradford/Nominal_NMPC

Nominal_NMPC

09 Apr 18:04
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Nominal_NMPC is a basic nonlinear model predictive control (NMPC) implementation in Python with soft constraints, which uses an Unscented Kalman filter for state estimation. The NMPC algorithm does not consider possible uncertainties and is therefore referred to as nominal. The dynamic equation system is assumed to be given by differential algebraic equations. The code is mostly meant to be used as a way to verify the performance of more novel algorithms against an implementation more likely to be found in industry.