A robust model predictive control scheme for a class of constrainednorm-bounded uncertain discrete-time linear systems is developed under thehypothesis that only partial state measurements are available for feedback.Off-line calculations are devoted to determining an admissible, though notoptimal, linear memoryless controller capable to formally address the inputrate constraint; then, during the on-line operations, predictive capabilitiescomplement the off-line controller by means of N steps free control actions ina receding horizon fashion. These additive control actions are obtained bysolving semi-definite programming problems subject to linear matrixinequalities constraints.
A Norm-Bounded based MPC strategy for uncertain systems under partial state availability
Valerio Scordamaglia
2018-01-01
Abstract
A robust model predictive control scheme for a class of constrainednorm-bounded uncertain discrete-time linear systems is developed under thehypothesis that only partial state measurements are available for feedback.Off-line calculations are devoted to determining an admissible, though notoptimal, linear memoryless controller capable to formally address the inputrate constraint; then, during the on-line operations, predictive capabilitiescomplement the off-line controller by means of N steps free control actions ina receding horizon fashion. These additive control actions are obtained bysolving semi-definite programming problems subject to linear matrixinequalities constraints.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
