Title :
A line search improvement of efficient MPC
Author :
Kouvaritakis, B. ; Shuang Li ; Cannon, M.
Author_Institution :
Dept. of Eng. Sci., Univ. of Oxford, Oxford, UK
fDate :
June 30 2010-July 2 2010
Abstract :
A recent lifting technique led to a computationally efficient Model Predictive Control (MPC) strategy in which the online optimization is performed using a univariate Newton-Raphson procedure. However this procedure solves a dual problem, preventing the use of warm starting or premature termination. By solving a primal problem, the current paper proposes a strategy that is more efficient than the Newton-Raphson method and enables warm starting and early termination. Extensive simulations show this to outperform the Newton-Raphson procedure and to have distinct advantages over alternative approaches based on quadratic programming or semidefinite programming.
Keywords :
Newton-Raphson method; predictive control; quadratic programming; Newton-Raphson method; lifting technique; line search improvement; model predictive control strategy; online optimization; premature termination; quadratic programming; semidefinite programming; warm starting; Computational modeling; Constraint optimization; Control system synthesis; Convergence; Cost function; Linear systems; Newton method; Predictive control; Predictive models; Quadratic programming; constrained control; optimization; predictive control for linear systems;
Conference_Titel :
American Control Conference (ACC), 2010
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-7426-4
DOI :
10.1109/ACC.2010.5531097