%T An algorithm for multi-parametric quadratic programming and explicit MPC solutions
%I IEEE
%P 1199-1204
%A Petter Tondel
%A Tor Arne Johansen
%A Alberto Bemporad
%L eprints581
%X Explicit solutions to constrained linear model-predictive control (MPC) problems can be obtained by solving multi-parametric quadratic programs (mp-QP) where the parameters are the components of the state vector. We study the properties of the polyhedral partition of the state space induced by the multi-parametric piecewise linear solution and propose a new mp-QP solver. Compared to existing algorithms, our approach adopts a different exploration strategy for subdividing the parameter space, avoiding unnecessary partitioning and QP problem solving, with a significant improvement in efficiency
%C Orlando, Florida USA, December 2001
%B Decision and Control Conference
%D 2001
%K constrained linear model-predictive control problems; efficiency; explicit solutions; exploration strategy; multi-parametric piecewise linear solution; multi-parametric quadratic programming algorithm; parameter space subdivision; partitioning; polyhedral state-space partition; problem solving; state vector components; piecewise linear techniques; predictive control; problem solving; quadratic programming; state-space methods
%R 10.1109/.2001.981048
%J Proc. 40th IEEE Conf. on Decision and Control
%V 2