Abstract:

Many of industrial processes belong to multivariable distributed parameter systems (DPS). Control of the DPS relies heavily on its analytical model. It is well-known that analytical modeling of the multivariable DPS is extremely difficult due to its complexity. It is always a challenging to estimate the spatial-temporal dynamics with limited sensing technology. In this presentation, fundamental philosophy of DPS modeling is discussed from the view of time-space separation. The existing computational modeling methods are briefly reviewed and compared for both known and unknown DPS. Finally, a hybrid intelligent methodology and a 3D Volterra series method are further proposed for the unknown DPS modeling. Using intelligent learning, the traditional modeling can be greatly enhanced. The curing oven is selected for implementation of all these intelligent approaches and demonstration of their strength. Finally a future challenge is discussed about the hybrid sub-domain modeling.

Biography：

Dr. HX Li received Ph.D. in electrical engineering from University of Auckland, New Zealand; M.E. in electrical engineering from Delft University of Technology in The Netherlands, and B.E. from National University of Defence Technology in China. Currently, he is a full professor in the Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong. He is a “Chang Jiang Scholar” in Central South University, China. He was awarded the distinguished young scholar fund by the China National Science Foundation in 2004. In last twenty years, he has opportunities to work in different fields including, military service, industry and academia. He has gained industrial experience as a senior process engineer from ASM – a leading supplier for semiconductor process equipment. His research interests include intelligent control and learning, process modelling and control, complex distributed parameter system and electronics packaging process. He serves as an associate editor for IEEE Transactions on Systems, Man & Cybernetics- part B.