A non-minimal state space formulation based predictive functional control design for inverse-response processes

• The non-minimal state space structure based on transfer function is presented.
• Corresponding predictive functional control algorithm is detailed.
• A detailed closed-loop analysis method for the nominal control system is provided for evaluating the control performances.

In this paper, the design of predictive functional control (PFC) based on non-minimal state space models is proposed for nonminimum phase processes referred to as inverse-response processes. The merits of the proposed method lie firstly in the fact that the measured input and output variables and their past values are chosen as the state variables that avoid the need of state observers. Secondly, by using the formulation of a new state space variable, the resulting PFC control incorporates both the state and output feedback, which further improve closed-loop process responses over previous methods. The performance and robustness of the control system are discussed. A typical example of inverse-response process is given to compare the proposed controller and the previous.