TY  - CHAP
TI  - An algorithm for multi-parametric quadratic programming and explicit MPC solutions
UR  - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=981048&isnumber=21128
A1  - Tondel, Petter
A1  - Johansen, Tor Arne
A1  - Bemporad, Alberto
Y1  - 2001///
SP  - 1199
ID  - eprints581
M1  - 2
AV  - none
SN  - 0-7803-7061-9 
CY  - Orlando, Florida USA, December 2001
T2  - Decision and Control Conference
PB  - IEEE
EP  - 1204
KW  - 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
N2  - 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
ER  -