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A perspective on nonlinear model predictive control
Lorenz Theodor Biegler 한국화학공학회 2021 Korean Journal of Chemical Engineering Vol.38 No.7
Model predictive control (MPC) is widely accepted as a generic multivariable controller with constraint handling. More recently, MPC has been extended to nonlinear model predictive control (NMPC) in order to realize high-performance control of highly nonlinear processes. In particular, NMPC allows incorporation of detailed process models (validated by off-line analysis) and also integrates with on-line optimization strategies consistent with higherlevel tasks, such as scheduling and planning. NMPC for tracking and so-called “economic” stage costs has been developed, and fundamental stability and robustness properties of NMPC have been analyzed. This perspective provides an overview of NMPC concepts and approaches, as well as the underlying optimization strategies that support the solution strategies. In addition, three challenging process case studies are presented to demonstrate the effectiveness of NMPC.
Efficient Algorithms for Exact Inference in Sequence Labeling SVMs
Bauer, Alexander,Gornitz, Nico,Biegler, Franziska,Muller, Klaus-Robert,Kloft, Marius IEEE 2014 IEEE transactions on neural networks and learning Vol.25 No.5
<P>The task of structured output prediction deals with learning general functional dependencies between arbitrary input and output spaces. In this context, two loss-sensitive formulations for maximum-margin training have been proposed in the literature, which are referred to as margin and slack rescaling, respectively. The latter is believed to be more accurate and easier to handle. Nevertheless, it is not popular due to the lack of known efficient inference algorithms; therefore, margin rescaling - which requires a similar type of inference as normal structured prediction - is the most often used approach. Focusing on the task of label sequence learning, we here define a general framework that can handle a large class of inference problems based on Hamming-like loss functions and the concept of decomposability for the underlying joint feature map. In particular, we present an efficient generic algorithm that can handle both rescaling approaches and is guaranteed to find an optimal solution in polynomial time.</P>
Smith, Robert L.,Young In Jhon,Biegler, Lorenz T.,Jhon, Myung S. IEEE 2013 IEEE transactions on magnetics Vol.49 No.7
<P>At the head disk interface (HDI), the stability of the perfluoropolyether (PFPE) lubricant and carbon overcoat (COC) materials must be preserved under HAMR conditions. In this work, we investigate this issue by comparing the effects of transient versus steady heating of Zdol to replicate the precise pulsed heating of the HAMR system. These effects include changes in intermolecular lubricant bonding, molecular decomposition and desorption. In order to accurately account for potential changes in covalent and intermolecular bonds, we utilize the cutting-edge molecular simulation method of ab initio molecular dynamics. To simulate constant heating, a series of constant temperature simulations are performed at temperatures ranging from 300 K-700 K where the temperature is maintained via the Nose Hoover thermostat. For the transient heating simulations, the temperature is ramped over 100 K intervals with initial temperatures ranging from 300 K to 700 K. These heating studies are performed for bulk PFPE systems as well as PFPE-COC configurations to highlight the effect of PFPE-COC adhesion on lubricant thermal stability at the HDI. In the PFPE-COC simulations, we evaluate the amount of desorption versus decomposition as a function of initial temperature. Through our analysis, we are able to reveal the molecular mechanism of PFPE depletion as a function of functional group composition and, thereby, provide design criteria for lubricant molecular architecture in HAMR applications.</P>
Perfluoropolyether Lubricant Interactions With Novel Overcoat via Coarse-Grained Molecular Dynamics
Vemuri, S. H.,Pil Seung Chung,Smith, R.,Geun-Young Yeom,Young In Jhon,Nae-Eung Lee,Biegler, L. T.,Jhon, M. S. IEEE 2012 IEEE transactions on magnetics Vol.48 No.11
<P>In this paper, we investigated physiochemical properties of new lubricant candidates for head-disk interface through various perfluoropolyether lubricant films on diamond, diamond-like carbon, and graphene overcoat surfaces via large scale coarse-grained bead-spring molecular dynamics stemming from the atomistic theory. Lubricant film conformations were characterized by investigating perpendicular component of molecular conformation, which determines the thickness of monolayer lubricant film. The distribution of functional endgroups and the mobility were analyzed via self-diffusion process. Here, we illustrate the effects of endgroup structure and carbon-surface structure on the film conformation and the mobility by expanding the multiscale simulation methodology and select candidates for future HDI design.</P>
Hierarchical Multiscale Modeling Method for Head/Disk Interface
Jhon, M S,Smith, R,Vemuri, S H,Pil Seung Chung,Dehee Kim,Biegler, L T IEEE 2011 IEEE transactions on magnetics Vol.47 No.1
<P>Multiscale modeling opens a new paradigm by providing a novel methodology of establishing molecular design criteria and potentially gives several orders of magnitude advances in nanotechnology. The head/disk interface (HDI) in the hard disk drive system investigated here can be used as a benchmark for multiscale modeling. Our approach, stemmed from the novel middle-out approach in modern multiscale modeling using the lattice Boltzmann method (LBM) as the centerpiece formulation, marches towards continuum level (top) and molecular level (bottom). This approach will become an extremely valuable tool in generating design criteria of HDI.</P>