Menu:
Data Driven Performance Assessment
The data driven economic performance assessment tool was developed in MATLAB® to allow data driven performance assessment of control loops. The programme was developed by the Computer Process Control Group at the University of Alberta.
In data driven performance assessment, the required benchmark is specified using a “good” data set for which the control is assumed to be properly regulating the process. All the other data sets are compared against this good data set. The advantages of this approach include that the optimal performance for a given system can be used as the benchmark and unnecessary or unfeasible changes are not implemented trying to achieve unachievable minimum variance control. As well, this method is not as calculationally intensive as no models of the system need to be determined. On the other hand, the main disadvantage of this approach is selecting an appropriate “good” data set.
The algorithm used by programme can be stated in the following steps:
- Determine the “good” data set and obtain the required information about the system.
- Gather routine operating data Y, the output, and U, the input.
- Calculate the values of p, r, and s for different lags i for both the good data set and th routine operating data.
- Plot the required curves for the data
- Compare the curves for the two data sets to determine the performance
Manual
The manual for using the toolbox can be found here.
System Requirements
This programme has the following prerequisites:
- Windows XP or newer. There may be issues with 64-bit Windows and the optimisation subroutines.
- 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®.
Download
The files can be downloaded from the Downloads section.
Developers
This software has been developed by the following people:
References
- Biao Huang, Steven X. Ding, and Nina Thornhill (2006). “Alternative Solutions to Multi-variate Feedback Control Performance Assessment Problems” in Journal of Process Control, Volume 16, pp. 457-471. doi: 10.1016/j.jprocont.2005.09.003