TY - GEN
T1 - Computational complexity reduction for robust model predictive control
AU - Feng, Le
AU - Wang, Jian Liang
AU - Poh, Eng Kee
PY - 2005
Y1 - 2005
N2 - Recently, it has been recognized that the dilation of the LMI characterizations has new potentials in dealing with such involved problems as multi-objective control, robust performance analysis or synthesis for real polytopic uncertainty and so on. In MPC area, Cuzzola et al. have proposed a technique which is based on the use of several Lyapunov functions each one corresponding to a different vertex of the uncertainty polytope. The main advantage of this approach with respect to the other wellknown techniques is the reduced conservativeness. However, this approach also increases the on-line computational complexity, which partially limits its practicality. In this paper, a novel approach by using convex combinations is addressed in order to reduce such on-line computational complexity substantially, with guaranteed robust stability of the closed-loop system, and by using the concept of the asymptotically stable invariant ellipsoids.
AB - Recently, it has been recognized that the dilation of the LMI characterizations has new potentials in dealing with such involved problems as multi-objective control, robust performance analysis or synthesis for real polytopic uncertainty and so on. In MPC area, Cuzzola et al. have proposed a technique which is based on the use of several Lyapunov functions each one corresponding to a different vertex of the uncertainty polytope. The main advantage of this approach with respect to the other wellknown techniques is the reduced conservativeness. However, this approach also increases the on-line computational complexity, which partially limits its practicality. In this paper, a novel approach by using convex combinations is addressed in order to reduce such on-line computational complexity substantially, with guaranteed robust stability of the closed-loop system, and by using the concept of the asymptotically stable invariant ellipsoids.
KW - Asymptotic stability
KW - Convex combinations
KW - Invariant ellipsoid
KW - Linear matrix inequalities
KW - Model Predictive Control
UR - http://www.scopus.com/inward/record.url?scp=27844527387&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:27844527387
SN - 0780391381
T3 - Proceedings of the 5th International Conference on Control and Automation, ICCA'05
SP - 522
EP - 527
BT - Proceedings of the 5th International Conference on Control and Automation, ICCA'05
T2 - 5th International Conference on Control and Automation, ICCA'05
Y2 - 27 June 2005 through 29 June 2005
ER -