Menu:
Univariate Performance Assessment (UVPA)
The Univariate Performance Assessment (UVPA) programme was developed to allow easy performance assessment of univariate (single input, single output) control loops by the Computer Process Control Group at the University of Alberta, which uses MATLAB and the Filtering and Correlation (FCOR) Algorithm to assess the performance of univariate processes.
Performance assessment was first developed by Dr. Thomas. J. Harris in 1989 by assuming that the control objective is to reduce process variance to a minimum. Minimum variance control is regarded as a benchmark, which provides information, such as how good the current controller performance is compared to the minimum variance case and how much potential there is to improve controller performance. If the performance index indicates good performance, further tuning or changes in the control algorithm may not necessary or helpful. On the other hand, if the performance index indicates poor performance, then further analysis is necessary to determine the root cause of the problems.
The algorithm used by programme can be stated in the following steps:
- First, closed-loop operating data without setpoint changes and the process time delay are required.
- Next, time-series analysis is performed to obtain an appropriate and stable model for the system.
- Then, the minimum variance for the process can be found from the infinite response of the closed-loop model.
- Finally, the performance index is the ratio of minimum variance to the actual, process variance.
Manual
The manual for using the toolbox can be found here.
System Requirements
This programme has the following prerequisites:
- Windows XP or newer.
- MATLAB® 2006a or newer. There may be issues with more recent (MATLAB® 2009a or newer) version of MATLAB®. The programme has not been tested on older versions of MATLAB®.
- System Identification Toolbox from MATLAB®.
Download
The files can be downloaded from the Downloads section.
Developers
This software has been developed by the following people:
References
- Biao Huang and Ramesh Kadali (2008). “Chapter 8: Control Loop Performance Assessment: Conventional Approach” in Dynamic Modeling, Predictive Control and Performance Monitoring: A Data-driven Subspace Approach. Springer Verlag, ISBN: 978-1-84800-232-6
- Biao Huang (2006). “Towards optimal MPC performance: industrial tools for multivariate control monitoring and diagnosis”, speech for Academic Viewpoint, SICOP Round Tables on Asset Management, International Workshop on Solving Industrial Control and Optimization Problems, Cramado, Brazil, April 6th-7th, 2006. Download copy.
- Biao Huang and Sirish Shah (1999). Performance Assessment of Control Loops. Springer Verlag, London ISBN: 978-1-85233-639-4
- Biao Huang (1997). Multivariate Statistical Methods for Control Loop Performance Assessment, PhD Thesis, University of Alberta. Download copy.