Impact of model plant mismatch on performance of control systems: An application to paper machine control

• Conducting a comprehensive study on performance monitoring of stochastic control systems, focusing on paper machines control.
• Analyzing effects of model–plant mismatch on closed-loop performance.
• Identifying conditions under which performance of each output in MIMO systems can be monitored separately.
• Quantifying sensitivity of the controller performance indices to model–plant mismatch.
• Improving the sensitivity of the performance indices to those types of model–plant mismatch with minimal effects on closed-loop performance during the regulatory model.

Model-based controllers based on incorrect estimates of the true plant behaviour can be expected to perform poorly. This work studies the effect of model plant mismatch on the closed loop behaviour and system performance for a certain class of MIMO systems. Performance is measured using a minimum variance index and a closely related user-specified criterion. We study the effect of model plant mismatch on the output variance and performance indices. Under mild assumptions, the performance of each output in a MIMO system can be analysed independently. Moreover, we propose an approach to distinguish the effect of model–plant mismatch from the effect of changes in disturbance characteristics on closed-loop performance. We define a sensitivity measure that relates system performance to model–plant mismatch, and use it to explore this sensitivity for three realistic types of parametric modelling errors. Next, we suggest a quantitative method that compares a system's actual output to its desired response in a transient setting. The performance of the transient response is demonstrably more sensitive to the model–plant mismatch than the steady state performance. The results are illustrated on industrial paper machine data.