Richard Braatz
University of Illinois
Department of Chemical & Biomolecular Engineering
University of Illinois
Urbana-Champaign
USA
The presentation will be given at 4.30 p.m., presumable in building 07, room 208.
Most high value products such as in the pharmaceuticals, microelectronic, and nanotechnology industries are manufactured in a series of processing steps that operate over finite time. These processes are usually distributed parameter systems in which tight control is required. Computationally efficient methods are proposed for the robust optimal control of finite-time distributed parameter systems (DPS), in which robustness is ensured for either deterministic or stochastic parametric uncertainties. In the deterministic case, the effects of uncertainties on the states and product quality are quantified by power series expansions combined with linear matrix inequality or structured singular value analysis. In the stochastic case, the effects of uncertainties are quantified by power series or polynomial chaos expansions followed by Monte Carlo simulation. The robust performance analysis have been incorporated into fixed or model predictive control algorithms. The approaches are illustrated for several applications problems.
Richard D. Braatz is Professor and Millennium Chair at the University of Illinois at Urbana-Champaign where he does research in the modeling, design, and control of chemical, pharmaceutical, and biomedical systems. He received MS and PhD degrees from the California Institute of Technology. Richard has consulted and/or collaborated with 15 companies including IBM, UTC Power, Eli Lilly, and Abbott Laboratories. Honors include the AACC Donald P. Eckman Award, ASEE Curtis W. McGraw Research Award, IEEE TCST Outstanding Paper Award, and Antonio Ruberti Young Researcher Prize. He is a Fellow of the Institute of Electrical and Electronics Engineers, the International Federation of Automatic Control, and the American Association for the Advancement of Science.