Exploiting Laguerre polynomials and steady-state estimates to facilitate tuning of PFC

Predictive Functional Control (PFC), a simplified and low-cost MPC algorithm, has gained considerable attention for industrial process control in the last two decades. Although with PFC, controller tuning is relatively simple and more meaningful than a PID controller, its efficacy turns poorer for larger prediction horizons–a necessity for over-damped ad nonminimum phase dynamics. This paper proposes a conceptually novel tuning mechanism based on a single choice which is: how much faster or slower than open-loop would you like the closed-loop to converge? Simulations demonstrate that this is a cheap and simple way of effective tuning, by suitably over or under actuating the open-loop control action