Generalized predictive controls over state space

Author

Park, Jung Hun ; Han, Soohee ; Kwon, Wook Hyun

Author_Institution

Seoul Nat. Univ., Seoul

fYear

2007

fDate

17-20 Sept. 2007

Firstpage

1281

Lastpage

1286

Abstract

In this paper, a generalized predictive control (GPC) is represented over state space and then is shown to be separated into the receding horizon control (RHC) and the steady-state Kalman filter. By utilizing only the information on the recent finite inputs and outputs, we propose a new finite memory GPC that consists of the RHC and a finite impulse response (FIR) filter. The proposed finite memory GPC will be compared with a conventional GPC for an input-output (I/O) model and the existing receding horizon finite memory control (RHFMC) for a state space model.

Keywords

FIR filters; Kalman filters; predictive control; state-space methods; finite impulse response filter; generalized predictive control; receding horizon finite memory control; state space model; steady-state Kalman filter; Computer science; Electronic mail; Finite impulse response filter; Predictive control; Predictive models; Process control; Robust stability; Stability analysis; State-space methods; Steady-state; Finite impulse response (FIR); Finite memory; Generalized predictive control (GPC); Input-output (I/O) model; Receding horizon control (RHC); State space model;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE, 2007 Annual Conference

Conference_Location

Takamatsu

Print_ISBN

978-4-907764-27-2

Electronic_ISBN

978-4-907764-27-2

Type

conf

DOI

10.1109/SICE.2007.4421181

Filename

4421181