Quadratic program solver for MPC using variable ordering
View Patent ↗A system and approach for storing factors in a quadratic programming solver of an embedded model predictive control platform. The solver may be connected to an optimization model which may be connected to a factorization module. The factorization module may incorporate a memory containing saved factors that may be connected to a factor search mechanism to find a nearest stored factor in the memory. A factor update unit may be connected to the factor search mechanism to obtain the nearest stored factor to perform a factor update. The factorization module may provide variable ordering to reduce a number of factors that need to be stored to permit the factors to be updated at zero floating point operations per unit of time.
1. A system for quadratic programming comprising:
an embedded platform comprising a model predictive control (MPC) controller connected to a physical subsystem; and
wherein the MPC controller comprises:
a state observer; and
a semi-explicit quadratic programming (QP) solver connected to the state observer; and
wherein the semi-explicit QP solver comprises:
an optimization module;
a factorization module connected to the QP optimization module;
wherein the factorization module comprises:
a memory having a saved factors unit;
a factor search mechanism connected to the saved factors unit; and
a factor update mechanism connected to the factor search mechanism; and
wherein the factorization module provides variable ordering to reduce factors which need to be stored to allow them to be updated at a zero floating-point operations per unit time (FLOPS) cost.
2. The system of claim 1 , wherein the physical subsystem comprises:
a physical plant;
one or more sensors situated at the physical plant and connected to the MPC controller; and
one or more actuators attached to the physical plant and connected to the MPC controller.
3. The system of claim 2 , wherein the physical plant is an internal combustion engine or after-treatment device.
4. The system of claim 1 , wherein the optimization module comprises a Karush-Kuhn-Tucker (KKT) subsystem having a KKT matrix.