Consideration about the stability and performance of a minimum variance control system
| Autor: | Octavian Prostean, Iosif Szeidert, Ioan Filip, Cristian Vasar |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
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 |
| Zdroj: | SACI |
| DOI: | 10.1109/saci49304.2020.9118827 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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