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- Juan Luis Jerez, Paul J. Goulart, Stefan Richter, George A. Constantinides, Eric C. Kerrigan, Manfred Morari
- IEEE Transactions on Automatic Control
- 2014

Faster, cheaper, and more power efficient optimization solvers than those currently possible using general-purpose techniques are required for extending the use of model predictive control (MPC) toâ€¦ (More)

- Juan Luis Jerez, Paul J. Goulart, Stefan Richter, George A. Constantinides, Eric C. Kerrigan, Manfred Morari
- 2013 European Control Conference (ECC)
- 2013

Model predictive control (MPC) in resource-constrained embedded platforms requires faster, cheaper and more power-efficient solvers for convex programs than is currently offered by software-basedâ€¦ (More)

- Juan Luis Jerez, Eric C. Kerrigan, George A. Constantinides
- Automatica
- 2012

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. We present aâ€¦ (More)

The succesful application of model predictive control (MPC) in fast embedded systems relies on faster and more energy efficient ways of solving complex optimization problems. A custom quadraticâ€¦ (More)

- Juan Luis Jerez, George A. Constantinides, Eric C. Kerrigan
- 2010 International Conference on Fieldâ€¦
- 2010

Automatic control, the process of measuring, computing, and applying an input to control the behaviour of a physical system, is ubiquitous in engineering and industry. Model predictive control (MPC)â€¦ (More)

- Juan Luis Jerez, George A. Constantinides, Eric C. Kerrigan
- IEEE Transactions on Computers
- 2015

We consider the problem of enabling fixed-point implementation of linear algebra kernels on low-cost embedded systems, as well as motivating more efficient computational architectures for scientificâ€¦ (More)

Model predictive control (MPC) is an advanced industrial control technique that relies on the solution of a quadratic programming (QP) problem at every sampling instant to determine the input actionâ€¦ (More)

- Edward N. Hartley, Juan Luis Jerez, Andrea Suardi, Jan M. Maciejowski, Eric C. Kerrigan, George A. Constantinides
- IEEE Transactions on Control Systems Technology
- 2014

Alternative and more efficient computational methods can extend the applicability of model predictive control (MPC) to systems with tight real-time requirements. This paper presents aâ€¦ (More)

In predictive control a nonlinear optimization problem has to be solved at each sample instant. Solving this optimization problem in a computationally efficient and numerically reliable fashion on anâ€¦ (More)

New embedded predictive control applications call for more efficient ways of solving quadratic programs (QPs) in order to meet demanding real-time, power and cost requirements. A single precisionâ€¦ (More)