Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Brief Explicit formulas for LMI-based H2 filtering and deconvolution
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Technical Communique: A synthesis approach of on-line constrained robust model predictive control
Automatica (Journal of IFAC)
Randomized Algorithms for Analysis and Control of Uncertain Systems: With Applications
Randomized Algorithms for Analysis and Control of Uncertain Systems: With Applications
An ellipsoidal off-line MPC scheme for uncertain polytopic discrete-time systems
Automatica (Journal of IFAC)
| Hi-index | 22.15 |
This paper presents a robustly stable finite-horizon model predictive control (MPC) scheme for linear uncertain systems, in which the uncertainty is not restricted to some specific uncertainty class (polytopic, affine, LFT, etc.). The only requirement is that the state-space matrices remain bounded over the uncertainty set. Suitable constraints are added to the MPC cost function to impose robust asymptotic stability and to deal with input/output constraints. The resulting optimization problem is solved at each time instant in a probabilistic framework using an iterative randomized ellipsoid algorithm (REA). The method is compared in simulation to the existing approach of Kothare, Balakrishnan and Morari [(1996). Robust constrained model predictive control using linear matrix inequalities. Automatica, 32(10), 1361-1379].