This paper presents a large-scale application of the normal vector approach to demonstrate that the complexity of robust dynamic optimization with application to the integration of process and control design can be treated successfully for complex nonlinear systems. The case study further demonstrates that our approach can deal with a multi-dimensional uncertainty space. The normal vector approach is able to automatically identify the worst-case scenarios and find a solution that is optimal with respect to the cost function and robust with respect to path constraints on inputs and states in the presence of parameterized disturbances. The tedious analysis of a large number of different disturbance realizations is not required.
|Número de páginas||5|
|Publicación||Computer Aided Chemical Engineering|
|Estado||Publicada - 2011|
|Publicado de forma externa||Sí|