Simultaneous Constrained Moving Horizon State Estimation and Model Predictive Control by Multi-Parametric Programming Conference Paper

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

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

authors

• Pistikopoulos, Stratos

published proceedings

• 49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC)

author list (cited authors)

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

citation count

• 10

complete list of authors

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

publication date

• December 2010

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Proceedings of the ... IEEE Conference on Decision & Control / IEEE Control Systems Society. IEEE Conference on Decision & Control  Journal

keywords

• Error Dynamics
• Mhe
• Moving Horizon Estimation
• Multi-parametric Programming
• Robust Explicit Mpc

Digital Object Identifier (DOI)

• 10.1109/CDC.2010.5717762

International Standard Book Number (ISBN) 13

• 9781424477456

start page

• 5019

end page

• 5024

URL

• http://dx.doi.org/10.1109/cdc.2010.5717762