Title :
Robustness and Identification Issues in Horizon Predictive Control With Application to a Binary Distillation Column
Author :
Rivera, D.E. ; Jun, K.S. ; Elisante, E. ; Sater, V.E. ; Horn, B.C.
Author_Institution :
Department of Chemical, Bio and Materials Engineering, Computer-Integrated Manufacturing Systems Research Center, Arizona State University, Tempe, Arizona 85287-6006; Control Systems Engineering Laboratory, Computer-Integrated Manufacturing Systems Resear
Abstract :
This paper analyzes the robustness properties and modeling requirements for model-predictive control via Horizon Predictive Control (HPC). The theory of Structured Singular Values is used to determine optimal values for the correction horizon in HPC given user-provided uncertainty intervals and performance weights. Regarding system identification, control-relevant identification principles are used to provide guidelines for input signal design, prefiltered estimation, and uncertainty modeling. These results are tested experimentally using data from a methanol-isopropanol distillation column.
Keywords :
Control system synthesis; Distillation equipment; Guidelines; Predictive control; Predictive models; Robust control; Signal design; System identification; Testing; Uncertainty;
Conference_Titel :
American Control Conference, 1992
Conference_Location :
Chicago, IL, USA
Print_ISBN :
0-7803-0210-9
