Journal article
On the Effects of Tunable Parameters of Model Predictive Control on the Locations of Closed-Loop Eigenvalues
Industrial & engineering chemistry research, v 49(17), pp 7951-7956
01 Sep 2010
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper presents an analytical study of the effects of model predictive control (MPC) tunable parameters on the closed-loop performance quantified in terms of the location(s) of closed-loop eigenvalue(s) of several common, single-input single-output, linear plants with inactive constraints. Symbolic manipulation capabilities of MATHEMATICA are used to obtain analytical expressions describing the dependence of closed-loop eigenvalues on the tunable parameters. This work is first to investigate how MPC tuning parameters affect the locations of the eigenvalues of the closed-loop system of a plant in the discrete-time setting. It provides theoretical basis/justification for several existing qualitative MPC tuning rules and proposes new tuning guidelines. For example, as the prediction horizon is increased while other tunable parameters remain constant, a subset of the closed-loop eigenvalues (poles) move toward the open-loop eigenvalues (poles) of the plant, if the plant is asymptotically stable. If a prediction horizon much longer than the reference-trajectory time constant is used, the value of the reference-trajectory time constant has little effect on the closed-loop performance. As the weights on the magnitude or the rate of change of the manipulated input are increased, the closed-loop eigenvalues move toward the open-loop eigenvalues. As the control horizon is increased from one, the dominant eigenvalue of the closed-loop system initially moves toward the origin and then away from the origin to a location that does not change with a further increase in the control horizon.
Metrics
Details
- Title
- On the Effects of Tunable Parameters of Model Predictive Control on the Locations of Closed-Loop Eigenvalues
- Creators
- Jorge L. Garriga - Drexel UniversityMasoud Soroush - Drexel UniversityH. M. Soroush - Kuwait University
- Publication Details
- Industrial & engineering chemistry research, v 49(17), pp 7951-7956
- Publisher
- American Chemical Society; Washington, DC
- Number of pages
- 6
- Grant note
- CBET-0651706 / National Science Foundation (NSF)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Chemical and Biological Engineering
- Web of Science ID
- WOS:000281107800023
- Scopus ID
- 2-s2.0-77956070410
- Other Identifier
- 991019168747304721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Engineering, Chemical