PV-based Model Predictive Control

An alternative method of Model Predictive Control called Process Value Model Predictive Control (PV-MPC) is presented that overcomes a number of the inherent problems in both set point and controller output MPC. The PV-MPC is based on process value (PV) as a manipulated variable in place of either set point (SP) or controller output (OP). This new MPC method utilizes PV-based models that are devoid of dynamic effects of the regulatory controllers and therefore eliminates model mismatch error arising from the regulatory controller tuning changes. With its embedded regulatory controllers, it compensates for unmeasured disturbance effects closest to the source while eliminating propagation of model mismatch error to other variables. It can operate with mix of fast to slow response time without loss of approximation with multiple control cycle frequency. It is immune from the adverse effects of model breakdown when a control valve saturates. It eliminates use of a whole class of models relating to controller output that are noisy and nonlinear and requires update of one model only for any change in control valve parameter. It can be upgraded with the least amount of changes for any process design change. The PV-based models can be identified with the least amount of plant testing. In comparison with the other two methods of MPC, the PV-MPC is much more robust, adaptable and efficient.