Persistently Exciting Model Predictive Control for SISO systems


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


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.