| While linear robust control theory is relatively well understood with many standard techniques for control system analysis and controller design, methods for designing robust nonlinear controllers are underdeveloped. This constitutes a significant gap in chemical process control theory, as real chemical processes have significant nonlinearities associated with their startup, shutdown, and normal operation.; The main objective of the present study is to develop a rigorous approach to design robust nonlinear controllers for chemical processes. The proposed design methodology integrates robust control theory results with nonlinearity inversion techniques. The proposed methodology is applied in a batch crystallization process. An identification and optimization procedure for a pharmaceutical, batch crystallization process is also presented, for complete understanding of the modeling issues entailed.; The controller design problem necessitates the solution of an optimization problem under bilinear matrix inequality constraints, which is a nonconvex optimization problem, has been shown to be NP-hard, and its efficient solution is also an open research problem. Various solution strategies have been incorporated to a branch and bound algorithm solving the aforementioned optimization problem, and were compared for various controller designs. |
