Tube-based anticipative model predictive control for linear parameter-varying systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)

Abstract

Currently available model predictive control methods for linear parameter-varying systems assume that the future behavior of the scheduling trajectory is unknown over the prediction horizon. In this paper, an anticipative tube MPC algorithm for polytopic linear parameter-varying systems under full state feedback is developed. In contrast to existing approaches, the method explicitly takes into account expected future variations in the scheduling variable: its current value is measured exactly, while the future values over the prediction horizon are assumed to belong to a sequence of sets describing expected deviations from a nominal trajectory. Through this mechanism, the controller “anticipates” upon future changes in the system dynamics. The algorithm constructs a tube homothetic to a terminal set and employs gain scheduled vertex control laws. A worst-case cost is minimized: the corresponding optimization problem is a single linear program with complexity linear in the prediction horizon. Numerical examples show the validity of the approach.
LanguageEnglish
Title of host publicationProceedings of the 55th Conference on Decision and Control, 12-14 December 2016, Las Vegas, USA
Pages1458-1463
DOIs
StatePublished - 2016
Event55th IEEE Conference on Decision and Control (CDC 2016) - Aria Resort and Casino, Las Vegas, United States
Duration: 12 Dec 201614 Dec 2016
Conference number: 55
http://cdc2016.ieeecss.org/

Conference

Conference55th IEEE Conference on Decision and Control (CDC 2016)
Abbreviated titleCDC02016
CountryUnited States
CityLas Vegas
Period12/12/1614/12/16
Internet address

Fingerprint

Model predictive control
Scheduling
Trajectories
State feedback
Dynamical systems
Controllers
Costs

Cite this

Hanema, J., Tóth, R., & Lazar, M. (2016). Tube-based anticipative model predictive control for linear parameter-varying systems. In Proceedings of the 55th Conference on Decision and Control, 12-14 December 2016, Las Vegas, USA (pp. 1458-1463). DOI: 10.1109/CDC.2016.7798472
Hanema, Jurre ; Tóth, Roland ; Lazar, Mircea. / Tube-based anticipative model predictive control for linear parameter-varying systems. Proceedings of the 55th Conference on Decision and Control, 12-14 December 2016, Las Vegas, USA. 2016. pp. 1458-1463
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abstract = "Currently available model predictive control methods for linear parameter-varying systems assume that the future behavior of the scheduling trajectory is unknown over the prediction horizon. In this paper, an anticipative tube MPC algorithm for polytopic linear parameter-varying systems under full state feedback is developed. In contrast to existing approaches, the method explicitly takes into account expected future variations in the scheduling variable: its current value is measured exactly, while the future values over the prediction horizon are assumed to belong to a sequence of sets describing expected deviations from a nominal trajectory. Through this mechanism, the controller “anticipates” upon future changes in the system dynamics. The algorithm constructs a tube homothetic to a terminal set and employs gain scheduled vertex control laws. A worst-case cost is minimized: the corresponding optimization problem is a single linear program with complexity linear in the prediction horizon. Numerical examples show the validity of the approach.",
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Hanema, J, Tóth, R & Lazar, M 2016, Tube-based anticipative model predictive control for linear parameter-varying systems. in Proceedings of the 55th Conference on Decision and Control, 12-14 December 2016, Las Vegas, USA. pp. 1458-1463, 55th IEEE Conference on Decision and Control (CDC 2016), Las Vegas, United States, 12/12/16. DOI: 10.1109/CDC.2016.7798472

Tube-based anticipative model predictive control for linear parameter-varying systems. / Hanema, Jurre; Tóth, Roland; Lazar, Mircea.

Proceedings of the 55th Conference on Decision and Control, 12-14 December 2016, Las Vegas, USA. 2016. p. 1458-1463.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AB - Currently available model predictive control methods for linear parameter-varying systems assume that the future behavior of the scheduling trajectory is unknown over the prediction horizon. In this paper, an anticipative tube MPC algorithm for polytopic linear parameter-varying systems under full state feedback is developed. In contrast to existing approaches, the method explicitly takes into account expected future variations in the scheduling variable: its current value is measured exactly, while the future values over the prediction horizon are assumed to belong to a sequence of sets describing expected deviations from a nominal trajectory. Through this mechanism, the controller “anticipates” upon future changes in the system dynamics. The algorithm constructs a tube homothetic to a terminal set and employs gain scheduled vertex control laws. A worst-case cost is minimized: the corresponding optimization problem is a single linear program with complexity linear in the prediction horizon. Numerical examples show the validity of the approach.

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Hanema J, Tóth R, Lazar M. Tube-based anticipative model predictive control for linear parameter-varying systems. In Proceedings of the 55th Conference on Decision and Control, 12-14 December 2016, Las Vegas, USA. 2016. p. 1458-1463. Available from, DOI: 10.1109/CDC.2016.7798472