Summary: Recently, inverse parametric linear/quadratic programming problem was shown to be solvable via convex liftings approach [N. A. Nguyen et al., “Inverse parametric convex programming problems via convex liftings”, IFAC Proc. Vol. 47, No. 3, 2489–2494 (2014; doi:10.3182/20140824-6-ZA-1003.02364)]. This technique turns out to be relevant in explicit model predictive control (MPC) design in terms of reducing the prediction horizon to at most two steps. In view of practical applications, typically leading to problems that are not directly invertible, we show how to adapt the inverse optimality to specific, possibly convexly non-liftable partitions. Case study results moreover indicate that such an extension leads to controllers of lower complexity without loss of optimality. Numerical data are also presented for illustration.
For the entire collection see [Zbl 1337.49003].