Adaptive discrepancy based control of particulate processes

This contribution is concerned with a relatively new approach to particulate process control. The main idea is to use of a generalized distance measure, the discrepancy, in order to describe deviations from a desired particle property distribution. Applying, the associated stability theory, i.e. stability theory with respect to two discrepancies, a stabilizing control law can be derived. One of the main advantages of the proposed discrepancy based control method is that no model reduction is required. In this contribution an adaptive extension of the discrepancy based control is proposed in order to control a crystallization process in the presence of parameter uncertainties.