Adaptive model predictive control for max-plus-linear discrete event input-output systems
Adaptive model predictive control for max-plus-linear discrete event input-output systems
- Author(s): T.J.J. van den Boom ; B. De Schutter ; G. Schullerus ; V. Krebs
- DOI: 10.1049/ip-cta:20040440
For access to this article, please select a purchase option:
Buy article PDF
Buy Knowledge Pack
IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.
Thank you
Your recommendation has been sent to your librarian.
- Author(s): T.J.J. van den Boom 1 ; B. De Schutter 1 ; G. Schullerus 2 ; V. Krebs 2
-
-
View affiliations
-
Affiliations:
1: Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands
2: Institut für Reglungs- und Steuerungssysteme, Universität Karlsruhe TH, Karlsruhe, Germany
-
Affiliations:
1: Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands
- Source:
Volume 151, Issue 3,
May 2004,
p.
339 – 346
DOI: 10.1049/ip-cta:20040440 , Print ISSN 1350-2379, Online ISSN 1359-7035
Model predictive control (MPC) is a popular controller design technique in the process industry. Conventional MPC uses linear or nonlinear discrete-time models. Recently, MPC has been extended to a class of discrete-event systems that can be described by a model that is ‘linear’ in max-plus algebra. An adaptive scheme for the time-varying case, based on parameter estimation of input-output models is presented. In a simulation example it is shown that the combined parameter-estimation/MPC algorithm gives a good closed-loop behaviour.
Inspec keywords: process control; algebra; predictive control; time-varying systems; closed loop systems; linear systems; discrete event systems; adaptive control; parameter estimation
Other keywords: adaptive model predictive control; input-output systems; max-plus algebra; process industry; max-plus-linear discrete event systems; parameter estimation
Subjects: Discrete control systems; Optimal control; Algebra; Simulation, modelling and identification; Self-adjusting control systems; Time-varying control systems
References
-
-
1)
- Schullerus, G., Krebs, V.: `A method for estimating the holding times in timed event graphs', Proc. 6th Workshop on Discrete Event Systems (WODES), 2002, Zaragossa, Spain, p. 119–124.
-
2)
- C.E. Garcia , D.M. Prett , M. Morari . Model predictive control: Theory and practice - a survey. Automatica , 3 , 335 - 348
-
3)
- E. Menguy , J.L. Boimond , L. Hardouin , J.L. Ferrier . A first step towards adaptive control for linear systems in max algebra. Discrete Event Dyn. Syst. Theory Appl. , 4 , 347 - 367
-
4)
- Schullerus, G., Krebs, V., van den Boom, T.J.J., De Schutter, B.: `Input signal design for max-plus-linear system identification using model predictive control', European Control Conf., Cambridge, UK, 2003, paper 26.
-
5)
- Y.C. Ho . (1992) Discrete event dynamic systems: analyzing complexity and performance in the modern world.
-
6)
- L. Ljung . (1999) System identification: theory for the user.
-
7)
- J.L. Boimond , J.L. Ferrier . Internal model control and max-algebra: controller design. IEEE Trans. Autom. Control , 3 , 457 - 461
-
8)
- De Schutter, B., van den Boom, T.J.J.: `Model predictive control for max-plus-linear systems', Proc. American Control Conf. 2000, June 2000, Chicago, IL, USA, p. 4046–4050.
-
9)
- T.J.J. van den Boom , B. De Schutter . Properties of MPC for max-plus-linear systems. Eur. J. Control , 5
-
10)
- Gallot, F., Boimond, J.L., Hardouin, L.: `Identification of simple elements in max-algebra: application to SISO discrete event systems modelisation', Proc. 4th European Control Conf., 1997, Brussels.
-
11)
- B. De Schutter , T. van den Boom . Model predictive control for max-plus-linear discrete event systems. Automatica , 7 , 1049 - 1056
-
12)
- K. Rudie , W.M. Wonham . Think globally, act locally: decentralized supervisory control. IEEE Trans. Autom. Control , 11 , 1692 - 1708
-
13)
- B. Heidergott , R. de Vries . Towards a (max,+) control theory for public transportation networks. Discrete Event Dyn. Syst. Theory Appl. , 4 , 371 - 398
-
14)
- Menguy, E.: `Contribution à la commande des systèmes linéaires dans les dioides', 1997, PhD thesis, Université d'Angers, Angers, France.
-
15)
- D.W. Clarke , C. Mohtadi , P.S. Tuffs . Generalized predictive control – Part I. The basic algorithm. Automatica , 2 , 137 - 148
-
16)
- R.A. Cuninghame-Green . (1979) Minimax algebra’, Lect. Notes Econ. Math. Syst..
-
17)
- C.G. Cassandras , S. Lafortune . (1999) Introduction to discrete event systems.
-
18)
- Libeaut, L., Loiseau, J.J.: `Admissible initial conditions and control of timed event graphs', Proc. 34th IEEE Conf. on Decision and Control, December 1995, New Orleans, LA, p. 2011–2016.
-
19)
- E. Menguy , J.L. Boimond , L. Hardouin , J.L. Ferrier . A first step towards adaptive control for linear systems in max algebra. Discrete Event Dyn. Syst. Theory Appl. , 4 , 347 - 368
-
20)
- E. Mosca . (1995) Optimal predictive and adaptive control.
-
21)
- P.J. Ramadge , W.M. Wonham . Supervisory control of a class of discrete-event processes. SIAM J. Control Optim. , 1 , 206 - 230
-
22)
- G. Cohen , S. Gaubert , J.P. Quadrat . Max-plus algebra and system theory: Where we are and where to go now. Ann. Rev. Control , 207 - 219
-
23)
- E.F. Camacho , C. Bordons . (1995) Model predictive control in the process industry, advances in industrial control.
-
24)
- J.M. Maciejowski . (2002) Predictive control with constraints.
-
25)
- F. Baccelli , G. Cohen , G.J. Olsder , J.P. Quadrat . (1992) Synchronization and linearity.
-
26)
- Menguy, E., Boimond, J.L., Hardouin, L.: `A feedback control in max-algebra', Presented at the European Control Conf. (ECC), July 1997, Brussels, Belgium, paper 487.
-
1)
Related content
