A combinatory study on MPC with subspace identification, steady-state target calculation and dynamic quadratic control

Author

Hongguang Pan ; Hainan Gao

Author_Institution

Dept. of Autom., Xi´an Jiaotong Univ., Xi´an, China

fYear

2014

Firstpage

3164

Lastpage

3169

Abstract

The prevailing industrial model predictive control (MPC) has two layers, i.e., the steady-state target calculation (SSTC) and the dynamic quadratic control. In this paper, it is suggested that the combination of subspace identification method (SIM) and double-layered MPC is a trend of the industrial process control. The multivariable output error state space (MOESP) method is adopted in SIM, and the multi priority rank method is designed in SSTC. This SIM-based double-layered MPC is illustrated through an example of the heavy oil fractionator model.

Keywords

control system synthesis; predictive control; process control; state-space methods; MOESP method; SIM; SSTC; double-layered MPC; dynamic quadratic control; heavy oil fractionator model; industrial process control; model predictive control; multipriority rank method; multivariable output error state space method; steady-state target calculation; subspace identification method; Heuristic algorithms; Matrix decomposition; Optimization; Process control; Steady-state; Target tracking; Zirconium; Dynamic control; Model predictive control; Steady-state calculation; Subspace identification method;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2014 11th World Congress on

Type

conf

DOI

10.1109/WCICA.2014.7053236

Filename

7053236