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.
A norm-bounded robust MPC strategy with partial state measurements / Franze, G.; Mattei, M.; Ollio, L.; Scordamaglia, V.. - 19:3(2014), pp. 7449-7454. (Intervento presentato al convegno 19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014 tenutosi a zaf nel 2014) [10.3182/20140824-6-za-1003.01702].
A norm-bounded robust MPC strategy with partial state measurements
Mattei M.;
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
