(503f) Predictive Control of Thin Film Deposition Using Stochastic Pdes
AIChE Annual Meeting
2005
2005 Annual Meeting
Multiscale Analysis in Chemical, Materials and Biological Processes
Hybrid Multiscale Simulation
Thursday, November 3, 2005 - 2:10pm to 2:30pm
This talk will discuss recent results on the construction of a 2-dimensional (2D) stochastic partial differential equation (PDE) model for a thin film deposition process and the design of a multivariable predictive controller based on the constructed model to control thin film thickness and surface roughness. Specifically, we focus on a thin film deposition process governed by three microscopic processes including molecule adsorption, migration and desorption. A 2D linear stochastic PDE model is initially constructed following a systematic model construction procedure that we recently proposed based on data obtained by a kinetic Monte-Carlo simulator of the process. Then, a multivariable predictive controller is designed using appropriate finite-dimensional approximations of the stochastic PDE model. The control problem is formulated as a predictive control problem, in which the finite-dimensional model is used to predict both the thin film thickness and the surface roughness. The model-based predictive controller is applied to the kinetic Monte-Carlo (kMC) simulation of the deposition process to simultaneously control the thin film thickness and surface roughness in the presence of manipulated input and state variable constraints. Closed-loop system simulation results demonstrate that the model is adequately accurate and that the controller is effective.