The problem in optimal control is to determine the control variable u(t) and the control (or design) parameters p in order to minimize an objective of Mayer type
(with a real-valued function 
).
The final time 
may be givend or free.
In order to obtain an approximation of the optimal control
a discretization of the control variable is applied.
Hereby, a time grid 
consisting
of NSGIT knots
is introduced.
The control is approximated by a continuous, piecewise linear function
over this time grid.
The values of the control variables at these knots
have to be determined in the optimization.
Also the inequality constraints (3) are discretized
by the algorithm in a similiar way.
They are satisfied at the times 
of the control discretization grid
The resulting nonlinearly constrained minimization problem is solved by a Sequential Quadratic Programming Method.
