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Consideration about the stability and performance of a minimum variance control system
- Source :
- SACI
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- This paper presents a stability and performance analysis of a self-tuning minimum variance control system. Designed through a cost function minimization, the control law is described by a linear difference model with time varying parameters. Based on a linearized process model around an operating point and by using a parameter estimator, the control system automatically adapts itself when process parameters change (as effect of a disturbance). However, the performance of the control system is strongly conditioned by an a priori setting of a factor that weights the control variance term of the cost function. The goal of this stability analysis is to provide a strategy regarding how to tune this control penalty factor, which significantly influences the stability and performance of the control system. Two approaches were considered: one based on the control system response in relation to the disturbance, validated by a second one based on frequency response analysis.
- Subjects :
- 0209 industrial biotechnology
Operating point
020208 electrical & electronic engineering
Stability (learning theory)
Process (computing)
Self-tuning
Estimator
02 engineering and technology
Variance (accounting)
020901 industrial engineering & automation
Minimum-variance unbiased estimator
Control theory
Control system
0202 electrical engineering, electronic engineering, information engineering
Mathematics
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI)
- Accession number :
- edsair.doi...........4c3e33e8e683a16e2e0e61fba255113b