Persistently Exciting Model Predictive Control for SISO systems

Citation:

G. Marafioti, Stoican, F., Hovd, M., and Bitmead, R. R., “Persistently Exciting Model Predictive Control for SISO systems”, in Proceedings of the 4th IFAC Nonlinear Model Predictive Control Conference, Noordwijkerhout, Netherlands, 2012, p. 448–453.

Date Published:

23-27 August

Abstract:

A formulation of Persistently Exciting Model Predictive Control (PE-MPC) for Single-Input Single-Output (SISO) systems is presented. PE-MPC is an extension of a conventional model predictive control where a Persistence of Excitation Condition (PEC) is included as inequality constraint, to allow for adaptive implementation and on-line tuning of the model. The PEC makes the PE-MPC feasible region non-convex. For SISO systems the non-convex region can be represented as the union of two convex regions. Therefore an ad-hoc solution of the PE-MPC optimization problem can be eciently computed. This is done by exploiting the particular structure of the PEC constraint. Finally a numerical example of SISO sytem is given and several scenarios are simulated to analyze the PE-MPC properties.

DOI:

10.3182/20120823-5-NL-3013.00054