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Abstract

An integrated optimization and control technique performs process control and optimization using stochastic optimization similar to that used in biological immune systems during on-line operation of a process, the technique collects and stores indications of process control states. During steady-state operation, the technique optimizes process operation by developing sets of process control inputs from stored process control states using an objective function that defines an optimality criterion. Moreover, after one or more disturbance inputs experiences a significant change, the technique responds by comparing the changed disturbance inputs to the disturbance inputs of at least some of the stored process control states to determine the stored process control states that are closest to the new process operating condition. The technique then develops a new set of control inputs based on the control inputs associated with the stored process control states determined to be closest to the new process operating condition.

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