Self-organizing migrating algorithm in model predictive control: Case study on semi-batch chemical reactor

Abstract

Control of complex nonlinear systems brings challenges in the controller design. One of methods how to cope with this challenge is the usage of advanced optimization methods. This work presents application of self-organizing migrating algorithm (SOMA) in control of the semi-batch reactor. The reactor is used in chromium recycling process in leather industry. Because of the complexity of this semi-batch reactor control, the model predictive control (MPC) approach is used. The MPC controller includes self-organizing migrating algorithm (SOMA) for the optimization of the control sequence.