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OpenOCL is now available as a .mltbx (Matlab toolbox package). Dependencies (CasADi, ipopt) will be downloaded and installed automatically for the most common systems.
Nlp now has block sparse structure. This should enable the use of better structure exploiting solvers. Ipopt's performance might improve as well. Parameters do not destroy the block sparsity structure.
- block sparse structure might be destroyed when boundary conditions on both x0 and xF are defined
With this new release we only support the new style of declaring systems and optimal control problems which means that systems are created by using function handles like
system = OclSystem(@varsfun, @eqfun);
you can also use named parameter list (in arbitrary order) like:
system = OclSystem('varsfun', @varsfun, 'eqfun'@eqfun);
The same holds for creating optimal control problems e.g.
ocp = OclOCP('arrivalcosts', @arrivalcosts, 'pathconstraints', @pathconstraints);
Have a look at the updated examples!