Simultaneous constrained Moving Horizon state Estimation and Model Predictive Control by multi-parametric programming Conference Paper uri icon

abstract

  • In this work, we demonstrate how constrained Moving Horizon Estimation (MHE) and Model Predictive Control (MPC) can be simultaneously addressed via multiparametric programming. First, we present a method for obtaining the error dynamics of constrained MHE for linear, time-invariant systems by solving the constrained optimization problem of the MHE by multi-parametric programming methods. Set-theoretical methods are then used to derive bounds on the estimation error - it is shown that the estimation error is bounded in an invariant set for the error dynamics described by a set of linear inequalities. The error dynamics and the error bounds can then be used for the design of a robust output feedback explicit/multi-parametric MPC yielding a simultaneous estimation and control design which is illustrated with an example of robust tube-based MPC. 2010 IEEE.

name of conference

  • 2010 49th IEEE Conference on Decision and Control (CDC)

published proceedings

  • 49th IEEE Conference on Decision and Control (CDC)

author list (cited authors)

  • Voelker, A., Kouramas, K., & Pistikopoulos, E. N.

citation count

  • 9

complete list of authors

  • Voelker, Anna||Kouramas, Konstantinos||Pistikopoulos, Efstratios N

publication date

  • December 2010

publisher