1.1.0

What's Changed

• Extend compatibility to CasADi 3.6.3 by @brunomorampc in #35
• Extended compatibility to Numpy 1.25.2 by @brunomorampc in #34

Full Changelog: v1.0.4...v1.1.0

1.0.3

Solved #16. Now the multi start does not take the results if the solver status is not either "solution found" or "solved to an acceptable level".

1.0.2

Fixes #11

1.0.1

Fixed bug with NMPC box constraints.
In a place there was x_lb instead of x_ub.

1.0.0

This is the initial release of HILO-MPC. HILO-MPC is a Python toolbox for easy, flexible, and fast realization of machine-learning-supported optimal control, and estimation problems. It can be used for model predictive control, moving horizon estimation, Kalman filters, solving optimal control problems, and has interfaces to embedded model predictive control tools.

Currently, the following machine learning models are supported:

• Feedforward neural networks
• Gaussian processes

At the moment the following MPC and optimal control problems can be solved:

• Reference tracking nonlinear MPC
• Trajectory tracking nonlinear MPC
• Path following nonlinear MPC
• Economic nonlinear MPC
• Linear MPC
• Traditional optimal control problems