Imperial College London > Talks@ee.imperial > CAS Talks > A Sparse and Condensed QP Formulation for Predictive Control

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## A Sparse and Condensed QP Formulation for Predictive ControlAdd to your list(s) Download to your calendar using vCal - Juan Jerez Fullana (Imperial College London)
- Tuesday 07 June 2011, 10:00-11:00
- Level 9 Mahanakorn Lab., EE Dept..
If you have a question about this talk, please contact Grigorios Mingas. The computational burden that model predictive control (MPC) imposes depends to a large extent on the way the optimal control problem is formulated as an optimization problem. When employing existing dense formulations the resulting optimization problem is small but the amount of computation grows cubically with the horizon length (one of the parameters of the control problem) due to dense matrix inversions. Existing sparse formulations result in larger problems that can be solved in time linear in the horizon length when exploiting the structure. In this talk, I will present a new formulation that uses a simple mathematical trick to introduce structure into the problem leading to compact and sparse optimization problems. The amount of computation required to solve the resulting optimization problem is smaller than with any of the two existing approaches for almost all control problems. This talk is part of the CAS Talks series. ## This talk is included in these lists:- Andrea Picciau's list
- CAS Talks
- Circuits and Systems Group: Internal Seminars
- Level 9 Mahanakorn Lab., EE Dept.
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