Control Design & Implementation

Digital Control of Dynamic Systems – Third Edition

Mar 24, 2022

This well-respected, market-leading text discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in...

Physics-informed Machine Learning for Control – DNN in a Dynamic Feedback Loop

Dec 6, 2021

This Case Study describes an approach to combining physical principles with Machine Learning (ML) for modeling and control of complex systems. Our approach was developed as part of a DARPA-funded research project. It was applied to oil reservoir management. While this Case Study provides an overview, technical details may be found in a separate publication [1].

Physics-informed Machine Learning for Control – DNN in a Dynamic Feedback Loop

Dec 6, 2021

This Case Study describes an approach to combining physical principles with Machine Learning (ML) for modeling and control of complex systems. Our approach was developed as part of a DARPA-funded research project. It was applied to oil reservoir management. While this...

Reactor-scale Modeling of Silicon Epitaxy

Oct 1, 2020

This case study of epitaxial deposition of silicon film on a silicon substrate in a horizontal hot-wall reactor reproduces an earlier modeling study by Habuka et al. [1]. The steady-state finite element (FEM) model incorporates fluid flow, heat transfer, dilute...

Temperature Control of Metal-Organic Chemical Vapor Disposition (MOCVD) Process

Oct 1, 2020

Physics-based MOCVD models are useful in many ways including model-based control, design of next-generation chambers, virtual sensing and process optimization. As a capability demonstration, SC Solutions has developed a finite element (FEM) model of a chamber shown...