Patent ID: 7577483

Claim:
A method of automarically tuning a multivariable model predictive controller (MPC) for a multivariable process that comprises the steps of: (a) identifying a process model for the multivariable process; (b) scaling inputs, which are manipulated variables, and outputs, which are controlled variables, of the process model; (c) calculating closed-loop transfer functions for performance and robustness as functions of tuning parameters for the MPC wherein the process model is used to calculate the closed-loop transfer functions or gain functions; (d) identifying at least one performance requirement for the MPC and transforming the at least one performance requirement into constraints on frequency responses of the closed-loop transfer functions or gain functions; (e) identifying at least one robustness requirement for the MPC and transforming the at least one robustness requirement into constraints on frequency responses of the closed-loop transfer functions or gain functions; (f) calculating possible ranges of tuning parameters such that a solution is known to exist within the range; (g) determining optimal tuning parameters with respect to performance and robustness; and (h) automatically yielding tuning parameters for the MPC based on performance and robustness requirements.