Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICARCV.2006.345196
Title: Improved robust model predictive control with structural uncertainty
Authors: Feng, L.
Wang, J.
Poh, E.
Liao, F. 
Keywords: Linear matrix inequalities
Model predictive control
Parameter dependent lyapunov function
Structured uncertainty
Issue Date: 2006
Citation: Feng, L.,Wang, J.,Poh, E.,Liao, F. (2006). Improved robust model predictive control with structural uncertainty. 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06 : -. ScholarBank@NUS Repository. https://doi.org/10.1109/ICARCV.2006.345196
Abstract: In this paper, a dilation of the LMI characterization is presented to address constrained robust model predictive control (MPC) for a class of uncertain linear systems with structured time-varying uncertainties. The uncertainty is described in linear fractional transformation (LFT) form. It is known such uncertain systems are popularly used in nonlinear system modeling and many other circumstances. By using parameter dependent Lyapunov functions, the designing conservativeness is reduced compared with some well-known MPC approaches. The proposed approach is applied to a two-mass-spring benchmark system to demonstrate the merits. © 2006 IEEE.
Source Title: 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06
URI: http://scholarbank.nus.edu.sg/handle/10635/115440
ISBN: 1424403421
DOI: 10.1109/ICARCV.2006.345196
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