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36 results on '"Munoz de la Pena, D."'

5. Interval Arithmetic in Robust Nonlinear MPC

Author

Limon, D., Alamo, T., Bravo, J. M., Camacho, E. F., Ramirez, D. R., Muñoz de la Peña, D., Alvarado, I., Arahal, M. R., Thoma, M., editor, Morari, M., editor, Findeisen, Rolf, editor, Allgöwer, Frank, editor, and Biegler, Lorenz T., editor

Published
2007
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6. A New Internet Tool for Automatic Evaluation in Control Systems and Programming

Author

Munoz de la Pena, D., Gomez-Estern, F., and Dormido, S.

Abstract

In this paper we present a web-based innovative education tool designed for automating the collection, evaluation and error detection in practical exercises assigned to computer programming and control engineering students. By using a student/instructor code-fusion architecture, the conceptual limits of multiple-choice tests are overcome by far. The proposed system is also able to individually parameterize the exercises for each student and allows an instructor to implement innovative self-learning techniques in which student can obtain a measure of their knowledge continuously along the whole course length. The proposed automatic evaluation system has been applied to several control engineering courses at the University of Seville and the results several case studies are presented here. (Contains 6 tables and 7 figures.)

Published
2012
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20. Further results on 'Robust MPC using Linear Matrix Inequalities'

Author

Lazar, M., Heemels, W.P.M.H., Munoz de la Pena, D., Alamo, T., Magni, L., Allgöwer, F., Raimondo, D.M., Control Systems, Constrained Control of Complex Systems, and Control Systems Technology

Subjects
Set (abstract data type), Model predictive control, Relation (database), Control theory, Linear system, Linear matrix inequality, A priori and a posteriori, Astrophysics::Cosmology and Extragalactic Astrophysics, Robust control, Hardware_REGISTER-TRANSFER-LEVELIMPLEMENTATION, Linear control, Mathematics
Abstract

This paper presents a novelmethod for designing the terminal cost and the auxiliary control law (ACL) for robust MPC of uncertain linear systems, such that ISS is a priori guaranteed for the closed-loop system. The method is based on the solution of a set of LMIs. An explicit relation is established between the proposed method and \(\mathcal{H}_\infty\) control design. This relation shows that the LMI-based optimal solution of the \(\mathcal{H}_\infty\) synthesis problem solves the terminal cost and ACL problem in inf-sup MPC, for a particular choice of the stage cost. This result, which was somehow missing in the MPC literature, is of general interest as it connects well known linear control problems to robust MPC design.

Published
2008

21. Design of ISS-Lyapunov functions for discrete-time linear uncertain systems

Author

Munoz de la Pena, D., Alamo, T., Lazar, M., Heemels, W.P.M.H., Cho, Hyung Suck, Control Systems, and Constrained Control of Complex Systems

Abstract

In this work we consider robust control of discrete-time linear systems affected by time-varying additive disturbance inputs. We present a linear matrix inequality (LMI) based design technique that takes into account in an explicit manner, by means of a Minkowski function, the shape of the set in which the disturbances are bounded. This technique allows one to obtain tight bounds on the performance of the closed-loop system.

Published
2008

22. Min-max nonlinear model predictive control with guaranteed input-to-state stability

Author

Lazar, M., Munoz de la Pena, D., Heemels, W.P.M.H., Alamo, T., Control Systems, and Constrained Control of Complex Systems

Abstract

—In this paper we consider discrete-time nonlinear systems that are affected, possibly simultaneously, by parametric uncertainties and disturbance inputs. The min-max model predictive control (MPC) methodology is employed to obtain a controller that robustly steers the state of the system towards a desired equilibrium. The aim is to provide a priori sufficient conditions for robust stability of the resulting closed-loop system via the input-to-state stability framework. First, we show that only input-to-state practical stability can be ensured in general for perturbed nonlinear systems in closed-loop with min-max MPC schemes and we provide explicit bounds on the evolution of the closed-loop system state. Then, we derive new sufficient conditions that guarantee input-to-state stability of the min-max MPC closedloop system, via a dual-mode approach. Keywords—Min-max, Nonlinear model predictive control, Input-to-state stability, Input-to-state practical stability

Published
2006

23. New Methods for Computing the Terminal Cost for Min-max Model Predictive Control

Author

Lazar, M., Munoz de la Pena, D., Heemels, W.P.M.H., Alamo, T., Lazar, M., Munoz de la Pena, D., Heemels, W.P.M.H., and Alamo, T.

Abstract

The aim of this paper is to provide new techniques for computing a terminal cost and a local state-feedback control law that satisfy recently developed min-max MPC input-to-state stabilization conditions. Min-max MPC algorithms based on both quadratic and 1-norms or infin-norms costs are considered. Compared to existing approaches, the proposed techniques can be applied to linear systems affected simultaneously by time-varying parametric uncertainties and additive disturbances. The resulting MPC cost function is continuous, convex and bounded, which is desirable from an optimization point of view. Regarding computational complexity aspects, the developed techniques employ linear matrix inequalities in the case of quadratic MPC cost functions and, norm inequalities in the case of MPC cost functions defined using 1-norms or infin-norms. The effectiveness of the developed methods is illustrated for an active suspension application example.

Published
2007

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