Design of enhanced two-dimensional self-optimizing control system for batch process

Abstract

In this paper, we design two-dimensional self-optimizing control (2D-SOC) systems for batch processes. In the framework of 2D-SOC, linear combinations of measurements are controlled along the time and batch axis, respectively, which work jointly to achieve near-optimal operation of batch process. Firstly, the global SOC approach is extended to enhance the self-optimizing performance in a wider range of disturbance space. In the presence of active-set changes, an improved solution method is presented to meet the constraint satisfactions. Then, a novel compensation algorithm is proposed to adjust the setpoints of within-batch controlled variables, which can efficiently improve the process optimality in the presence of tracking errors of batch-to-batch controlled variables and active constraint back-offs. A simple linear compensation law is optimally derived. Finally, the enhanced 2D-SOC design approach is systematically applied to two simulated batch processes, where its enhanced performances are verified.