S. Qin and T. Badgwell, A survey of industrial model predictive control technology, Control Engineering Practice, vol.11, issue.7, pp.733-764, 2003.
DOI : 10.1016/S0967-0661(02)00186-7

D. Niederberger, Hybrid systems: computation and control Design of optimal autonomous switching circuits to suppress mechanical vibration, pp.511-525, 2005.

A. G. Wills, D. Bates, A. J. Fleming, B. Ninness, and S. O. Moheimani, Model Predictive Control Applied to Constraint Handling in Active Noise and Vibration Control, IEEE Transactions on Control Systems Technology, vol.16, issue.1, pp.3-12, 2008.
DOI : 10.1109/TCST.2007.903062

URL : http://www.eng.newcastle.edu.au/~ajf203/PDFs/J08b.pdf

A. Wills, A. Mills, and B. Ninness, FPGA Implementation of an Interior-Point Solution for Linear Model Predictive Control*, IFAC Proc. Volumes World Congress, pp.14-527, 2011.
DOI : 10.3182/20110828-6-IT-1002.02857

G. Takács and B. Rohal-'-ilkiv, Model Predictive Vibration Control: Efficient Constrained MPC Vibration Control for Lightly Damped Mechanical Structures
DOI : 10.1007/978-1-4471-2333-0

C. Edwards, The 8-bit strikes back, Electronics Systems and Software, vol.5, issue.2, pp.36-39, 2007.
DOI : 10.1049/ess:20070207

P. Busono, A. Iswahyudi, M. A. Rahman, and A. Fitrianto, Design of Embedded Microcontroller for Controlling and Monitoring Blood Pump, Procedia Computer Science, vol.72, pp.217-224, 2015.
DOI : 10.1016/j.procs.2015.12.134

D. K. Kufoalor, V. Aaker, T. A. Johansen, L. Imsland, and G. O. Eikrem, Automatically generated embedded model predictive control: Moving an industrial PC-based MPC to an embedded platform, Optimal Control Applications and Methods, vol.59, issue.1, pp.705-727, 2015.
DOI : 10.1109/TAC.2013.2275667

P. Dua, K. Kouramas, V. Dua, and E. Pistikopoulos, MPC on a chip???Recent advances on the application of multi-parametric model-based control, Computers & Chemical Engineering, vol.32, issue.4-5, pp.754-765, 2008.
DOI : 10.1016/j.compchemeng.2007.03.008

B. Huyck, J. D. Brabanter, B. D. Moor, J. F. Impe, and F. Logist, Online model predictive control of industrial processes using low level control hardware: A pilot-scale distillation column case study, Control Engineering Practice, vol.28, pp.34-48, 2014.
DOI : 10.1016/j.conengprac.2014.02.016

D. K. Kufoalor, S. Richter, L. Imsland, T. A. Johansen, M. Morari et al., Embedded Model Predictive Control on a PLC using a primal-dual first-order method for a subsea separation process, 22nd Mediterranean Conference on Control and Automation, pp.368-373, 2014.
DOI : 10.1109/MED.2014.6961399

K. Ling, B. Wu, and J. Maciejowski, Embedded Model Predictive Control (MPC) using a FPGA, IFAC Proc. Volumes 17th IFAC World Congress, pp.15-250, 2008.
DOI : 10.3182/20080706-5-KR-1001.02579

P. D. Vouzis, L. G. Bleris, M. G. Arnold, and M. V. Kothare, A System-on-a-Chip Implementation for Embedded Real-Time Model Predictive Control, IEEE Transactions on Control Systems Technology, vol.17, issue.5, pp.1006-1017, 2009.
DOI : 10.1109/TCST.2008.2004503

D. Q. Mayne, Model predictive control: Recent developments and future promise, Automatica, vol.50, issue.12, pp.2967-2986, 2014.
DOI : 10.1016/j.automatica.2014.10.128

S. Richter, C. Jones, and M. Morari, Real-time input-constrained MPC using fast gradient methods, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, pp.7387-7393, 2009.
DOI : 10.1109/CDC.2009.5400619

URL : https://infoscience.epfl.ch/record/169743/files/cdc09_richter.pdf

P. Zometa, M. Kögel, T. Faulwasser, and R. Findeisen, Implementation aspects of model predictive control for embedded systems, 2012 American Control Conference (ACC), pp.1205-1210
DOI : 10.1109/ACC.2012.6315076

J. L. Jerez, P. J. Goulart, S. Richter, G. A. Constantinides, E. C. Kerrigan et al., Embedded Online Optimization for Model Predictive Control at Megahertz Rates, IEEE Transactions on Automatic Control, vol.59, issue.12, pp.3238-3251, 2014.
DOI : 10.1109/TAC.2014.2351991

URL : http://arxiv.org/pdf/1303.1090

A. Bemporad, M. Morari, V. Dua, and E. N. Pistikopoulos, The explicit linear quadratic regulator for constrained systems, Automatica, vol.38, issue.1, pp.3-20, 2002.
DOI : 10.1016/S0005-1098(01)00174-1

A. Alessio and A. Bemporad, Asurvey on explicit model predictive control , " in Nonlinear Model Predictive Control: Towards New Challenging, pp.345-369, 2009.

F. Borrelli, Constrained Optimal Control of Linear and Hybrid Systems, 2003.

M. Kvasnica, Real-Time Model Predictive Control via Multi-Parametric Programming: Theory and Tools, 2009.

A. Pneumont, Vibration Control of Active Structures: An Introduction, 2011.

R. Oberdieck, N. A. Diangelakis, I. Nascu, M. M. Papathanasiou, M. Sun et al., On multi-parametric programming and its applications in process systems engineering, Chemical Engineering Research and Design, vol.116, 2016.
DOI : 10.1016/j.cherd.2016.09.034

G. Takács and B. Rohal-'-ilkiv, Model predictive control algorithms for active vibration control: a study on timing, performance and implementation properties, Journal of Vibration and Control, vol.20, issue.13, pp.2061-2080, 2014.
DOI : 10.1109/TCST.2007.903062

G. Takács, G. Batista, M. Gulan, and B. Rohal-'-ilkiv, Embedded explicit model predictive vibration control, Mechatronics, vol.36, pp.54-62, 2016.
DOI : 10.1016/j.mechatronics.2016.04.008

N. A. Nguyen, S. Olaru, P. Rodríguez-ayerbe, and M. Kvasnica, Convex liftings-based robust control design, Automatica, vol.77, pp.206-213, 2017.
DOI : 10.1016/j.automatica.2016.11.031

URL : https://hal.archives-ouvertes.fr/hal-01509316

N. A. Nguyen, S. Olaru, P. Rodríguez-ayerbe, M. Hovd, and I. Necoara, Constructive Solution of Inverse Parametric Linear/Quadratic Programming Problems, Journal of Optimization Theory and Applications, vol.36, issue.9, pp.1-26, 2016.
DOI : 10.1109/9.83532

URL : https://hal.archives-ouvertes.fr/hal-01408472

M. Gulan, N. A. Nguyen, S. Olaru, P. Rodríguez-ayerbe, and B. Rohal-'-ilkiv, Implications of Inverse Parametric Optimization in Model Predictive Control, Develop. in Model-Based Optim. and Control: Distrib. Control and, pp.49-70, 2015.
DOI : 10.1016/S0005-1098(02)00250-9

URL : https://hal.archives-ouvertes.fr/hal-01259959

E. C. Kerrigan, Robust constraint satisfaction: invariant sets and predictive control, 2000.

J. Richelot, J. Bordeneuve-guibe, and V. Pommier-budinger, Active Control of a clamped beam equipped with piezoelectric actuator and sensor using generalized predictive control, 2004 IEEE International Symposium on Industrial Electronics, pp.583-588, 2004.
DOI : 10.1109/ISIE.2004.1571872

G. Ferrari and M. Amabili, Active vibration control of a sandwich plate by non-collocated positive position feedback, Journal of Sound and Vibration, vol.342, pp.44-56, 2015.
DOI : 10.1016/j.jsv.2014.12.019

D. J. Inman, Engineering Vibrations, 2014.

R. Y. Chiang and M. G. Safonov, Design of H? controller for a lightly damped system using a bilinear pole shifting transform, Proc. Amer. Control Conf, pp.1927-1928, 1991.

F. Blanchini and S. Miani, Set-Theoretic Methods in Control, Birkhäuser Boston, 2008.
DOI : 10.1007/978-3-319-17933-9

M. Kvasnica, J. Hledík, I. Rauová, and M. Fikar, Complexity reduction of explicit model predictive control via separation, Automatica, vol.49, issue.6, pp.1776-1781, 2013.
DOI : 10.1016/j.automatica.2013.02.018

F. Bayat, T. A. Johansen, and A. A. Jalali, Flexible Piecewise Function Evaluation Methods Based on Truncated Binary Search Trees and Lattice Representation in Explicit MPC, Convex liftings: theory and control applications, pp.632-640, 2012.
DOI : 10.1109/TCST.2011.2141134

J. Spjøtvold, E. C. Kerrigan, C. N. Jones, P. Tøndel, and T. A. Johansen, On the facet-to-facet property of solutions to convex parametric quadratic programs, Automatica, vol.42, issue.12, pp.2209-2214, 2006.
DOI : 10.1016/j.automatica.2006.06.026

N. A. Nguyen, Explicit robust constrained control for linear systems: analysis, implementation and design based on optimization, 2015.
URL : https://hal.archives-ouvertes.fr/tel-01261034

M. Kvasnica and M. Fikar, Clipping-Based Complexity Reduction in Explicit MPC, IEEE Transactions on Automatic Control, vol.57, issue.7, pp.1878-1883, 2012.
DOI : 10.1109/TAC.2011.2179428

N. A. Nguyen, S. Olaru, P. Rodríguez-ayerbe, M. Hovd, and I. Necoara, Inverse parametric convex programming problems via convex liftings, IFAC Proc. Volumes IFAC World Congress, pp.2489-2494, 2014.
DOI : 10.3182/20140824-6-ZA-1003.02364

URL : https://hal.archives-ouvertes.fr/hal-01086492

M. Baoti´cbaoti´c, F. Borrelli, A. Bemporad, and M. Morari, Efficient On-Line Computation of Constrained Optimal Control, SIAM Journal on Control and Optimization, vol.47, issue.5, pp.2470-2489, 2008.
DOI : 10.1137/060659314

F. Bayat, T. A. Johansen, and A. A. Jalali, Using hash tables to manage the time-storage complexity in a point location problem: Application to explicit model predictive control, Automatica, vol.47, issue.3, pp.571-577, 2011.
DOI : 10.1016/j.automatica.2011.01.009

M. Kvasnica, B. Takács, J. Holaza, and S. D. Cairano, On region-free explicit model predictive control, 2015 54th IEEE Conference on Decision and Control (CDC), pp.3669-3674, 2015.
DOI : 10.1109/CDC.2015.7402788

A. Gupta, S. Bhartiya, and P. Nataraj, A novel approach to multiparametric quadratic programming, Automatica, vol.47, issue.9, pp.2112-2117, 2011.
DOI : 10.1016/j.automatica.2011.06.019

F. Borrelli, M. Baoti´cbaoti´c, J. Pekar, and G. Stewart, On the computation of linear model predictive control laws, Automatica, vol.46, issue.6, pp.1035-1041, 2010.
DOI : 10.1016/j.automatica.2010.02.031

A. Airan, M. Bhushan, and S. Bhartiya, Linear Machine Solution to Point Location Problem, IEEE Transactions on Automatic Control, vol.62, issue.3, pp.1403-1410, 2017.
DOI : 10.1109/TAC.2016.2573201

M. Herceg, M. Kvasnica, C. N. Jones, and M. Morari, Multi-parametric toolbox 3.0, Proc. 12th Eur. Control Conf, pp.502-510, 2013.

J. Löfberg, YALMIP: a toolbox for modeling and optimization in MAT- LAB, IEEE Int. Symp. Comput. Aided Control Syst. Design, pp.284-289, 2004.

G. Takács, P. Zometa, R. Findeisen, and B. Rohal-'-ilkiv, Efficiency and performance of embedded model predictive control for active vibration attenuation, 2016 European Control Conference (ECC), pp.1334-1340, 2016.
DOI : 10.1109/ECC.2016.7810474

N. A. Nguyen, S. Olaru, P. Rodríguez-ayerbe, G. Bitsoris, and M. Hovd, Explicit robustness and fragility margins for linear discrete systems with piecewise affine control law, Automatica, vol.68, pp.334-343, 2016.
DOI : 10.1016/j.automatica.2015.10.048

URL : https://hal.archives-ouvertes.fr/hal-01408554

G. Takács, 11) received both the M.Sc. and Ph.D. degrees in mechatronics from the Slovak University of Technology in Bratislava he was a Research Assistant with the Institute of Automation Since 2015, he has been an Associate Professor with the same university His research interests include optimal control and estimation, active vibration control and embedded systems, 2006.

N. A. Nguyen-received-a-double and M. Sc, degree in electrical engineering from the Hanoi University of Science and Technology, Vietnam, and from the Grenoble Institute of Technology, France, in 2012 His main research interests lie in optimization-based control and set-theoretic methods, 2015 he received his Ph.D. degree at the Laboratory of Signals and Systems Since 2016, he has been a Post-Doctoral Scholar with the Johannes Kepler University

. Supélec, CNRS Laboratory of Signals and Systems and of the INRIA team DISCO ?all these institutions being part of the Paris-Saclay University, France. His research interests encompass optimization-based control design, set-theoretic characterization of constrained dynamical systems as well as numerical methods in control. He is currently involved in research projects related to embedded predictive control, fault tolerant control and time-delay systems

P. Rodríguez-ayerbe, 10) received the M.Sc. degree in electrical engineering from École Supérieure d'Électricité (Supélec), Gif-sur-Yvette, France, in 1996. He then received the Ph.D. degree in automatic control and the HDR degree from Supélec and the University Paris-Sud, 2002.

B. Rohal-'-ilkiv, 11) received both the M.Sc. degree and the Ph.D. degree in technical cybernetics from the Slovak University of Technology in Bratislava His main research interests lie in optimizationbased estimation and control of industrial processes and mechatronic systems, including combustion engines , underactuated mechanical systems and active vibration systems, Since 2003 he has been a Professor in mechatronics with the Institute of Automation, Measurement and Applied Informatics, 1972.