Performance Assessment of Control Loops

The main concern of this thesis is to assess control loop performance using minimum variance control by FCOR algorithm in a convenient way by using only routine operating data and comparing the outcomes with an existing algorithm (named PINDEX). Only by determining a performance factor of the feed-back control loop the controller performance could be assessed, even from thousands of control loops in process industries. Minimum variance is the benchmark which indicates attainable minimum variance against the actual variance of the control error. A performance index has been defined as the ratio of minimum variance to actual variance. Where, a performance index value close to 1 indicates good control a value close to 0 indicates poor control. The performance index is always bounded between 0 to1. The performance index calculation algorithm was implemented using MATLAB. A dynamic simulation study was performed using Aspen HYSIS for generating process data and also by SIMULINK. Various cases such as noise corruption, stiction and oscillation were introduced and the aftermath was studied and analyzed. Industrial data from an Ammonia plant (SAFCO) was also analyzed. All the results are compared with previously developed algorithm. This thesis will help to outline a very simple but effective way to detect performance of the controller in process systems.