Stability Analysis of Quadratic MPC With a Discrete Input Alphabet

Author

Aguilera, Ricardo P. ; Quevedo, D.E.

Author_Institution

Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Newcastle, NSW, Australia

Volume

58

Issue

12

fYear

2013

fDate

Dec. 2013

Firstpage

3190

Lastpage

3196

Abstract

We study stability of Model Predictive Control (MPC) with a quadratic cost function for LTI systems with a discrete input alphabet. Since this kind of systems may present a steady-state error, the focus is on practical stability, i.e., ultimate boundedness of solutions. To derive sufficient conditions for practical stability and characterize the ultimately invariant set, we analyze the one-step horizon solution and adapt tools used for convex MPC formulations.

Keywords

discrete systems; linear systems; predictive control; set theory; stability; LTI systems; convex MPC formulations; discrete input alphabet; linear time-invariant systems; model predictive control; one-step horizon solution; practical stability; quadratic MPC; quadratic cost function; stability analysis; steady-state error; sufficient conditions; ultimate boundedness; Asymptotic stability; Cost function; Hidden Markov models; Mathematical model; Quantization (signal); Signal processing algorithms; Stability analysis; Finite sets; practical stability; predictive control; quantized systems;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/TAC.2013.2264551

Filename

6517884