Patent Document ID: 7650195
Application ID: 11260809
Patent Flag: 1

Claim One:
1. A method of automatically tuning a multivariable model predictive controller (MPC) for a spatially-distributed process that comprises the steps of: (a) identifying a process model for the spatially-distributed process, that includes process measurements and actuations, which is part of a closed-loop MPC control system; (b) scaling inputs and outputs of the process model in the spatial frequency domain to yield a scaled process model by (i) transforming the process model into a series or matrix models or subplants, (ii) finding spatial controllable components for each subplants, (iii) averaging the subplants to yield an average model that represents the process model and (iv) finally, finding scaling input and output functions of the average model, wherein scaling comprises one input scaling number for each actuator array and one output scaling number for each measurement array to mitigate the effects of physical unit changes and changes in spatial resolution of process measurements and actuations and whereby sealing the inputs and outputs of the process model causes tuning parameters not to change with physical unit changes of measurement and actuation and causes tuning parameters not to change with resolution changes of measurement and actuation; (c) transforming the scaled process model into a two-dimensional frequency domain; (d) transforming the MPC into a two-dimensional frequency domain; (e) determining an optimal solution of the spatial tuning parameters with respect to model uncertainty which comprises first calculating possible ranges of the spatial tuning parameters for the MPC and then searching in the spatial frequency domain for stabilizing the closed-loop system due to model uncertainty and which satisfies a robust, stability condition in the spatial frequency domain; (f) determining an optimal solution of the temporal tuning parameters with respect to model uncertainty which comprises first calculating possible ranges of the temporal parameters for the MPC and then searching in the temporal frequency domain for stabilizing the closed-loop system due to model uncertainty and which satisfies a robust stability condition in the temporal frequency domain; and (g) repeating steps (e) and (f) in an iterative process until suitable spatial tuning parameters und temporal tuning parameters are determined such that the spatially-distributed process as part of a closed-loop MPC control system exhibits robust stability and whereby tuning is done automatically in the two-dimensional frequency domain, wherein the spatially-distributed process is a sheetmaking cross-directional (CD) process.