Unrestricted horizon predictive control applied to a nonlinear SISO system

This paper presents the mathematical formalism, design and evaluation of a minimum order unrestricted horizon predictive control (UHPC) predictive applied to nonlinear chemical process. The UHPC design method is still quite new and this paper contributes further by evaluating its application in a nonlinear system and its robustness properties. The control design is done to ensure stability, robustness, reference tracking and disturbance rejection even in the presence of modeling errors and noise. The evaluation is conducted through numerical simulations for step references and load disturbances with one single system: the continuous stirred tank reactor (CSTR). The UHPC problem are assessed under an incremental control scheme and based on the identified stochastic linear model. The temporal and frequency results of the UHPC are compared to the results of the generalized predictive control (GPC) using the same output prediction horizon. Both controllers are able to eliminate the offset, however the UHPC has greater margins of stability and noise attenuation, being able to maintain the same loop response throughout the control system’s operating range, without degrading the performance of the controller, which is not the case with GPC.