Adaptive multivariable MPC controller with LP constraints

A method for creating an adaptive multivariable controller for controlling a process having a plurality of independently controllable, manipulated variables, some of which are provided by the solution to a separate linear program, and at least one controlled variable dependent upon said independently controllable, manipulated variables comprising the steps of:

• gathering data about said process by separately introducing test disturbances in each of said manipulated variables and measuring the effect of the disturbances on said controlled variable;
• using said effects of the disturbances on said controlled variable to generate a first linearized dynamic model relating said at least one controlled variable to said independently controllable, manipulated variables;
• interchanging the final control position controlled variables with their corresponding selected independently controllable, manipulated PID controller set point variables in said first linearized dynamic model using matrix row elimination mathematics to generate a second linearized dynamic model that has a new set of independently controllable, manipulated variables, said second linearized dynamic model having said selected independently controllable, manipulated PID controller set point variables removed from said second linearized dynamic model;
• measuring the present value of said variables;
• wherein said second linearized dynamic model is the adaptive multivariable controller ready for adaptive control;
• pre-setting operating limits for said at least one controlled variable;
• pre-setting test limits for said at least one controlled variable that fall within said operating limits;
• using the second linearized dynamic model to calculate a first set of prediction vectors for said at least one controllable variable;
• placing said second linearized dynamic model in an adaptive test mode wherein all of the PID controllers are switched to manual;
• perturbing the final control element manipulated variables with random excitation signals;
• calculating for discrete intervals of time from said gathered data about said process, said measured present values and pre-selected operating constraints a set of moves for present and future times for at least said manipulated variables to obtain new values for said manipulated variables and to move said at least one dependent controllable variable towards at least one of said constraints;
• when the linear program solution is infeasible, setting each PID set-point that is outside of its corresponding pre-set operating limits at said corresponding pre-set operating limit;
• and
• when the prediction vector is outside of test limits for said at least one controlled variable, changing said process by adjusting said manipulated variables for said set of moves for present and future times to cause said process to move said at least one dependent controllable variable towards at least one of said constraints.