-This paper outlines a method to implement nonlinear model predictive control (NMPC) in real-time control applications.Nonlinear model identification is generally seen as a major obstacle to implementing NMPC. However, once an accurate nonlinear model is identified the computational effort is often too great to implement the model in a real-time application. The approach in this paper is a two step process, model reduction followed by computational reduction. Model reduction is accomplished by computing balanced empirical gramians. Computational reduction is accomplished by using the method of in situ adaptive tabulation (ISAT).ISAT was previously developed for computational reduction of turbulent flame direct numerical simulations and is extended to the sequential NMPC framework in this work. A case study is performed with a binary distillation column model with 32 states. By computing balanced empirical gramians the number of states is reduced to five. With ISAT, the computational speed is 85 times faster than the original NMPC while maintaining the accuracy of the nonlinear model. Since ISAT is a storage and retrieval method, it is compared to artificial neural networks in another case study. This case study is performed with a dual CSTR model with 6 states. Open loop and closed loop step tests are performed to demonstrate the superior quality of ISAT in extrapolating outside of the training domain.
<p>Understanding the physical and chemical properties of viral infection at molecular scales is a major challenge of the scientific community in the fight against the Coronavirus (COVID-19) pandemic. We employ all-atoms molecular dynamics simulations to study the interaction between the receptor-binding domain of the SARS-CoV-2 spike protein and the surfactant lecithin in water solutions. Our microsecond simulations reveal a preferential binding of lecithin to the receptor-binding motif (RBM) of SARS-CoV-2. Furthermore, we find that the lecitin-RBM binding events are mainly dominated by the hydrophobic interactions, which are accompanied by dewetting of water molecules near the RBM. These proof-of-concept simulations provide a demonstration of the use of biodegradable phospholipids as blockers of binding of SARS-CoV-2 with the human Angiotensin-Converting Enzyme 2 (ACE2) receptor.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.