<abstract xmlns="http://www.w3.org/1999/xhtml"><p> This paper presents an alternative approach to the task of control performance assessment. Various statistical measures based on Gaussian and non-Gaussian distribution functions are evaluated. The analysis starts with the review of control error histograms followed by their statistical analysis using probability distribution functions. Simulation results obtained for a control system with the generalized predictive controller algorithm are considered. The proposed approach using Cauchy and Lévy α-stable distributions shows robustness against disturbances and enables effective control loop quality evaluation. Tests of the predictive algorithm prove its ability to detect the impact of the main controller parameters, such as the model gain, the dynamics or the prediction horizon.</p></abstract>

This paper presents an alternative approach to the task of control performance assessment. Various statistical measures based on Gaussian and non-Gaussian distribution functions are evaluated. The analysis starts with the review of control error histograms followed by their statistical analysis using probability distribution functions. Simulation results obtained for a control system with the generalized predictive controller algorithm are considered. The proposed approach using Cauchy and Lévy α-stable distributions shows robustness against disturbances and enables effective control loop quality evaluation. Tests of the predictive algorithm prove its ability to detect the impact of the main controller parameters, such as the model gain, the dynamics or the prediction horizon.

Assessment of the GPC Control Quality Using Non–Gaussian Statistical Measures

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

This paper presents an alternative approach to the task of control performance assessment. Various statistical measures based on Gaussian and non-Gaussian...

Assessment of the GPC Control Quality Using Non–Gaussian Statistical Measures

Online veröffentlicht: 08. Juli 2017

Seitenbereich: 291 - 307

Eingereicht: 11. Mai 2016

Akzeptiert: 12. Jan. 2017

DOI: https://doi.org/10.1515/amcs-2017-0021

Schlüsselwörter
control performance assessment, GPC control, non-Gaussian PDF, Cauchy PDF, Lévy α-stable PDF

© by Maciej Ławryńczuk

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Assessment of the GPC Control Quality Using Non–Gaussian Statistical Measures

Online veröffentlicht: 08. Juli 2017

Seitenbereich: 291 - 307

Eingereicht: 11. Mai 2016

Akzeptiert: 12. Jan. 2017

DOI: https://doi.org/10.1515/amcs-2017-0021

Schlüsselwörtercontrol performance assessment, GPC control, non-Gaussian PDF, Cauchy PDF, Lévy α-stable PDF

© by Maciej Ławryńczuk

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
control performance assessment, GPC control, non-Gaussian PDF, Cauchy PDF, Lévy α-stable PDF