Activities per year
Abstract
Currently available model predictive control methods for linear parametervarying 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 parametervarying 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 worstcase 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.
Original language  English 

Title of host publication  Proceedings of the 55th Conference on Decision and Control, 1214 December 2016, Las Vegas, USA 
Pages  14581463 
DOIs  
Publication status  Published  2016 
Event  55th IEEE Conference on Decision and Control (CDC 2016)  Aria Resort and Casino, Las Vegas, United States Duration: 12 Dec 2016 → 14 Dec 2016 Conference number: 55 http://cdc2016.ieeecss.org/ 
Conference
Conference  55th IEEE Conference on Decision and Control (CDC 2016) 

Abbreviated title  CDC02016 
Country  United States 
City  Las Vegas 
Period  12/12/16 → 14/12/16 
Internet address 
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Activities
 1 Contributed talk

55th IEEE Conference on Decision and Control (CDC 2016), 1214 December 2016, Las Vegas, USA
Jurre Hanema (Speaker)
12 Dec 2016 → 14 Dec 2016Activity: Talk or presentation types › Contributed talk › Scientific