### Abstract

This paper describes a model predictive control (MPC) approach for discrete-time linear systems with hard constraints on control and state variables. The finite-horizon optimal control problem is formulated as a quadratic program (QP), and solved using a recently proposed dual fast gradient-projection method. More precisely, in a finite number of iterations of the mentioned optimization algorithm, a solution with bounded levels of infeasibility and suboptimality is determined for an alternative problem. This solution is shown to be a feasible suboptimal solution for the original problem, leading to exponential stability of the closed-loop system. The proposed strategy is particularly useful in embedded control applications, for which real-time constraints and limited computing resources can impose tight bounds on the possible number of iterations that can be performed within the scheduled sampling time.

Original language | English |
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Title of host publication | 2013 European Control Conference, ECC 2013 |

Pages | 3065-3070 |

Number of pages | 6 |

Publication status | Published - 2013 |

Event | 2013 12th European Control Conference, ECC 2013 - Zurich, Switzerland Duration: Jul 17 2013 → Jul 19 2013 |

### Conference

Conference | 2013 12th European Control Conference, ECC 2013 |
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Country | Switzerland |

City | Zurich |

Period | 7/17/13 → 7/19/13 |

### Fingerprint

### ASJC Scopus subject areas

- Control and Systems Engineering

### Cite this

*2013 European Control Conference, ECC 2013*(pp. 3065-3070). [6669435]

**Stabilizing embedded MPC with computational complexity guarantees.** / Rubagotti, Matteo; Patrinos, Panagiotis; Bemporad, Alberto.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*2013 European Control Conference, ECC 2013.*, 6669435, pp. 3065-3070, 2013 12th European Control Conference, ECC 2013, Zurich, Switzerland, 7/17/13.

}

TY - GEN

T1 - Stabilizing embedded MPC with computational complexity guarantees

AU - Rubagotti, Matteo

AU - Patrinos, Panagiotis

AU - Bemporad, Alberto

PY - 2013

Y1 - 2013

N2 - This paper describes a model predictive control (MPC) approach for discrete-time linear systems with hard constraints on control and state variables. The finite-horizon optimal control problem is formulated as a quadratic program (QP), and solved using a recently proposed dual fast gradient-projection method. More precisely, in a finite number of iterations of the mentioned optimization algorithm, a solution with bounded levels of infeasibility and suboptimality is determined for an alternative problem. This solution is shown to be a feasible suboptimal solution for the original problem, leading to exponential stability of the closed-loop system. The proposed strategy is particularly useful in embedded control applications, for which real-time constraints and limited computing resources can impose tight bounds on the possible number of iterations that can be performed within the scheduled sampling time.

AB - This paper describes a model predictive control (MPC) approach for discrete-time linear systems with hard constraints on control and state variables. The finite-horizon optimal control problem is formulated as a quadratic program (QP), and solved using a recently proposed dual fast gradient-projection method. More precisely, in a finite number of iterations of the mentioned optimization algorithm, a solution with bounded levels of infeasibility and suboptimality is determined for an alternative problem. This solution is shown to be a feasible suboptimal solution for the original problem, leading to exponential stability of the closed-loop system. The proposed strategy is particularly useful in embedded control applications, for which real-time constraints and limited computing resources can impose tight bounds on the possible number of iterations that can be performed within the scheduled sampling time.

UR - http://www.scopus.com/inward/record.url?scp=84893294073&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84893294073&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84893294073

SN - 9783033039629

SP - 3065

EP - 3070

BT - 2013 European Control Conference, ECC 2013

ER -