The simultaneous saccharification and fermentation (SSF) approach is an industrially important paradigm for the production of cellulosic ethanol. This study proposes to develop and implement a low cost adaptive model predictive control framework which efficiently manages multi-rate measurements, environmental perturbations and feed-grade transitions.These goals will be achieved by integrating exit gas analysis based sensors (ethanol, O2, CO2) and an online FT-NIR spectroscopy system (for characterizing the hydrolysis products) into the proposed control framework.Identifying the extent to which an instrumented and controlled process would reduce dependency on enzyme costs, as well as facilitate robustness to process fluctuations is one of the main focus of the project. (Sponsors: Dept. of Bio-Technology, Govt. of India)

This work explored possibility of developing nonlinear data driven block oriented black box models with Wiener / Hammerstein / Wiener - Hammerstein structurefor capturing nonlinear dynamics of a Fluidized Bed Reactor (FBR) system. These models were parametrized using generalized orthonormal basis filter (GOBF). In particular, design procedure was evolved for generating plant friendly input excitation signal to obtain the input-output data such that the identified black box model reveals salient nonlinear features of FBR system. Modeling studies indicated that GOBF-Wiener models were able to capture features of steady state and dynamic nonlinearities satisfactorily. Multiple nonlinear model based framework was also investigated for modeling grade transitions in the FBR system. (Sponsors: Honeywell Technology Solutions Lab, Bangalore)