0.6.1

Fixed

• Fixed the horizon slicing for the non-linear mpc. The horizon slicing was not working properly when set via the HorizonSlice struct

0.6.0

Added

• Added support for input and state bound constraints in the non-linear mpc. These constraints are actually restricing the search space of the optimization problem
  and are obeyed by the solver also during intermediate steps of the optimization problem
• Added warm start support in the non-linear mpc. The warm start is disabled by default and can be enabled using the parameter enable_warm_start

Changed

• Breaking change: The stopping criterias in the non-linear mpc parameters are now disabled by default. The only enabled criteria is the maximum number of iterations
• Breaking change: The optimal sequence returned by the linear and non-linear mpc is now containing also the initial condition
• The Jacobians of the constraints in the non-linear mpc are now estimated using the trapeizoial rule
• The functions to set the bound constraints now uses a dedicated structure to define the horizon span
• Breaking change: The functions setConstraints are now split in setStateBounds, setInputBounds and setOutputBounds
• Breaking change: The fields retcode and status_msg in the result struct of the non-linear mpc are now solver_status and solver_status_msg respectively

0.5.0

Added

• Python bindings for the library using pybind11 (pympcxx)
• The result struct now contains a string to describe the status of the optimization problem
• Added new parameters for the nonlinear mpc (time_limit, absolute_ftol, absolute_xtol)

Changed

• Breaking change: some of the APIs have been refactored. New APIs: setDiscretizationSamplingTime, setExogenousInputs, optimize
  substitute setContinuosTimeModel, setExogenuosInputs, step
• Improved error handling in the NLopt interface

Fixed

• The set of the discretization sampling time was not working properly in the non-linear mpc

0.4.2

Added

• Added examples to show how to use the library

Fixed

• Fixed the cmake target configuration to properly target the library

0.4.1

Changed

• Removed coloured output for the integrated logger
• Configure script now can be used to avoid the installation of the test suite

Fixed

• Fixed dockerfile to use the 0.6.3 version of the OSQP solver

0.4.0

Added

• Added profiler to measure statistics of the optimization problem
• In linear mpc is now possible to override the warm start of the optimization problem
• Added support for OSQP warm start in linear mpc

Changed

• The linear mpc parameters now allows enabling the warm start of the optimization problem
• The mpc result structure now contains a status field to check if the optimization problem has been solved
• CMakelists.txt has been refactored to export the INCLUDE_DIRS variable

0.3.1

Fixed

• The computation of the scalar multipler was not correct

0.3.0

Added

• Added new api in linear mpc to add a scalar constraints

Changed

• In linear mpc the last input command is now used to initialize the optimal control problem

Fixed

• The default value for the box constraints in linear mpc are now set -inf and inf
• In linear mpc optimal input sequence was erroneously the delta input sequence

0.2.0

Added

• Improved performances of non-linear mpc

Changed

• Added support in non-linear for output penalization in the objective function (Breaking change)
• In non-linear prediction step index is now available in the model update function (Breaking change)

0.1.0

Added

• Added support in linear mpc to define the references, weights, constraints and exogenous inputs different in each prediction step
• Added general support to the retrival of the optimal sequence (state, input and output)

Changed

• The API to set the references, weights constraints and exogenous inputs using vector now requires a span of the horizon (Breaking changes)
• Added new APIs to define the references, weights, constraints and exogenous inputs matrices to the whole horizon
• Internal structure of the library has been refactored to separate non-linear and linear classes