In this work, we focus on the problem of monitoring and retuning of low-level proportional-integral-derivative (PID) control loops used to regulate control actuators to the values computed by advanced model-based control systems like model predictive control (MPC). We consider the case where the real-time measurement of the actuation level is unavailable, and thus PID controller monitoring has to be achieved on the basis of process state measurements. A fault detection and isolation (FDI) method involving process models and real-time process measurements is used to monitor the PID control loops and compute appropriate residuals. Once poor tuning is detected and isolated, a PID tuning method based on the estimated transfer function of the control actuator is applied to the isolated, poorly functioning PID controller. An example of a non-linear reactor-separator process operating under MPC with low-level PID controllers regulating the control actuators is used to demonstrate the approach. (C) 2011 Elsevier Ltd. All rights reserved.