In this paper a robust MPC scheme based on a partial-state availability is developed for uncertain discrete-time linear systems described by structured norm-bounded model uncertainties and subject to saturation and rate of variation constraints. The algorithm is based on the minimization, at each time instant, of a semi-definite convex optimization problem subject to Linear Matrix Inequalities (LMI) feasibility constraints which are derived by a judicious use of S-Procedure arguments. Numerical comparisons with competitor algorithms are finally reported by dealing with the control augmentation problem of an High Altitude Performance Demonstrator (HAPD) unmanned aircraft with redundant control surfaces. © IFAC.
A norm-bounded robust MPC strategy with partial state measurements
MATTEI, Massimiliano;
2014
Abstract
In this paper a robust MPC scheme based on a partial-state availability is developed for uncertain discrete-time linear systems described by structured norm-bounded model uncertainties and subject to saturation and rate of variation constraints. The algorithm is based on the minimization, at each time instant, of a semi-definite convex optimization problem subject to Linear Matrix Inequalities (LMI) feasibility constraints which are derived by a judicious use of S-Procedure arguments. Numerical comparisons with competitor algorithms are finally reported by dealing with the control augmentation problem of an High Altitude Performance Demonstrator (HAPD) unmanned aircraft with redundant control surfaces. © IFAC.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
