A convex parameterization for solving constrained min-max problems with a quadratic cost

Proceedings of the American Control Conference

Volumn 3, Issue , 2004, Pages 2220-2221

  Kerrigan, Eric C ^a,c   Alamo, Teodoro ^b  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^b UNIVERSITY OF SEVILLE   (Spain)

^c ROYAL ACADEMY OF ENGINEERING   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; COST EFFECTIVENESS; FUNCTIONS; LINEAR CONTROL SYSTEMS; PARAMETER ESTIMATION; QUADRATIC PROGRAMMING; SET THEORY;

FEEDBACK POLICY; PARAMETERIZATION; QUADRATIC COSTS;

PROBLEM SOLVING;

EID: 8744258591     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.23919/acc.2004.1383791     Document Type: Conference Paper

References (4)

1. A. Ben-Tal, A. Goryashko, E. Guslitzer, and A. Nemirovski, "Adjustable robust solutions of uncertain linear programs," Technion (Israel Institute of Technology), Haifa, Israel, Tech. Rep., 2002, downloadable from http://iew3.technion.ac.il/Labs/Opt/index.php?4.
2. E. C. Kerrigan and J. M. Maciejowski, "Properties of a new parameterization for the control of constrained systems with disturbances," in Proc. 2004 American Control Conference, Boston, MA, USA, June 2004.
3. J. Löfberg, "Approximations of closed-loop minimax MPC," in Proc. 42nd IEEE Conference on Decision and Control, Maui, HI, USA, December 2003.
4. D. Q. Mayne, J. B. Rawlings, C. V. Rao, and P. O. M. Scokaert, "Constrained model predictive control: Stability and optimality," Automatica, vol. 36, pp. 789-814, 2000, survey paper.