This paper describes a hierarchical scheme for the control of independent stable systems subject to joint constraints. At the higher layer of the control structure reduced order dynamic models are used to minimize an economic cost function by adopting a long sampling time, while at the lower layer independent shrinking horizon MPC controllers working at a faster rate are designed for the original models to guarantee stability and convergence. A novel model reduction procedure is developed and simulation results are reported to witness the potentialities of the approach.

Hierarchical Model Predictive Control of independent systems with joint constraints

PICASSO, BRUNO;ZHANG, XINGLONG;SCATTOLINI, RICCARDO
2016

Abstract

This paper describes a hierarchical scheme for the control of independent stable systems subject to joint constraints. At the higher layer of the control structure reduced order dynamic models are used to minimize an economic cost function by adopting a long sampling time, while at the lower layer independent shrinking horizon MPC controllers working at a faster rate are designed for the original models to guarantee stability and convergence. A novel model reduction procedure is developed and simulation results are reported to witness the potentialities of the approach.
Hierarchical control; Model predictive control; Model reduction; Control and Systems Engineering; Electrical and Electronic Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1009254
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