Iterative solutions

An alternative to the explicit solution could be to use an iterative solution to solve the QP problem (S0rdalen, 1997). The drawback with the iterative solution is that several iterations may have to be performed at each sample in order to find the optimal solution. The iterative approach is more flexibility for on-line reconfiguration, as for example a change in W may require that the explicit solutions are recalculated. Computational complexity is also greatly reduced by a warm start-i.e., the numerical solver is initialized with the solution of the optimization problem computed at the previous sample.

Finally, the offline computed complexity and memory requirements may be prohibited for the explicit solution to be applicable to large scale control allocation problems.

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