Bilinear Compensated Predictive Controller: A state variables approach

Nonlinear Predictive Control has been subject of many researches in recent decades. Bilinear models have been an alternative to represent process nonlinearities because they are simpler than the nonlinear models in general and satisfactorily represent many types of nonlinearities. This paper presents a state variables approach of bilinear predictive control. This approach uses a compensated state variables model obtained from the compensated polynomial model, which uses a quasilinear model with the addition of compensations terms to the predictor model. These terms are different for each prediction horizon. A simulated example shows an improvement in the control performance by using this method, when it is compared with the "time-step quasilinear predictive controller".