Implementable model predictive control in the state space

Model predictive control is an optimal control based method for constrained feedback control. Previous work at The University of Texas at Austin has focussed on the development of model predictive controllers that are nominally asymptotically stable for all valid tuning parameters. This development eliminated the need for tuning to obtain nominal stability. However, some implementation issues were not addressed. This work provides a discussion of those issues and solutions that allow the application of a nominally stable linear model predictive controller to be more easily realized in practice. The algorithms discussed in this work are implemented using Octave´s (1993) high level interactive language and can be easily translated into other programming languages