Deterministic optimization based control system and method for linear and non-linear systems

摘要

The embodiments described herein include one embodiment that provides a control method including determining a linear approximation of a pre-determined non-linear model of a process to be controlled, determining a convex approximation of the nonlinear constraint set, determining an initial stabilizing feasible control trajectory for a plurality of sample periods of a control trajectory, executing an optimization-based control algorithm to improve the initial stabilizing feasible control trajectory for a plurality of sample periods of a control trajectory, and controlling the controlled process by application.

主权项

1. A method for controlling operation of an automation system, comprising:
determining, using a control system, a first linear approximation of a non-linear model configured to model non-linear operation of the automation system; determining, using the control system, a first convex approximation of a nonlinear constraint on the operation of the automation system; performing, using the control system, a first quadratic transformation on an objective function; performing, using the control system, a first optimization search based at least in part on the first linear approximation, the first convex approximation, and the objective function after the first quadratic transformation is performed to determine a first feasible trajectory of a manipulated variable of the automation system over a plurality of sample periods in a first control horizon; and instructing, using the control system, the automation system to adjust the operation based at least in part on the first feasible trajectory of the manipulated variable; wherein determining the first convex approximation comprises: determining a second convex approximation of the nonlinear constraint; determining a third convex approximation of the nonlinear constraint; determining amount of an infeasible region that does not satisfy the nonlinear constraint included in the second convex approximation and the third convex approximation; determining amount of a feasible region that satisfies the nonlinear constraint included in the second convex approximation and the third convex approximation; setting the first convex approximation as the second convex approximation or the third convex approximation based at least in part on amount of the feasible region included in the second convex approximation, amount of the feasible region included in the third convex approximation, amount of the infeasible region included in the second convex approximation, and amount of the infeasible region included in the third convex approximation; wherein the first convex approximation comprises simple bounds.