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Richard D. Braatz
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2020 – today
- 2023
- [j65]Pavan K. Inguva
, Richard D. Braatz
:
Efficient numerical schemes for multidimensional population balance models. Comput. Chem. Eng. 170: 108095 (2023) - [j64]Prakitr Srisuma, Ajinkya Pandit
, Qihang Zhang, Moo Sun Hong, Janaka Gamekkanda, Fabio Fachin, Nathan Moore, Dragan Djordjevic, Michael Schwärzler
, Tolutola Oyetunde, Wenlong Tang, Allan S. Myerson, George Barbastathis
, Richard D. Braatz
:
Thermal imaging-based state estimation of a Stefan problem with application to cell thawing. Comput. Chem. Eng. 173: 108179 (2023) - [j63]Anastasia Nikolakopoulou, Richard D. Braatz
:
Polynomial NARX-based nonlinear model predictive control of modular chemical systems. Comput. Chem. Eng. 177: 108272 (2023) - [j62]Prakitr Srisuma, George Barbastathis
, Richard D. Braatz
:
Analytical solutions for the modeling, optimization, and control of microwave-assisted freeze drying. Comput. Chem. Eng. 177: 108318 (2023) - [j61]Yiming Wan
, Dongying E. Shen
, Sergio Lucia
, Rolf Findeisen
, Richard D. Braatz
:
A Polynomial Chaos Approach to Robust Static Output-Feedback Control With Bounded Truncation Error. IEEE Trans. Autom. Control. 68(1): 470-477 (2023) - [c99]Janine Matschek, Marc D. Berliner, Andreas Himmel, Richard D. Braatz, Rolf Findeisen:
Necessary Optimality Conditions for Fast Lithium-ion Battery Charging via Hybrid Simulations. ACC 2023: 3783-3789 - [c98]Roland Schurig, Andreas Himmel, Amer Mesanovic, Richard D. Braatz, Rolf Findeisen:
Estimating Parameter Regions for Structured Parameter Tuning via Reduced Order Subsystem Models. ACC 2023: 3809-3814 - [i10]Joachim Schaeffer, Paul Gasper, Esteban García Tamayo, Raymond Gasper, Masaki Adachi, Juan Pablo Gaviria-Cardona, Simon Montoya-Bedoya, Anoushka Bhutani, Andrew Schiek, Rhys Goodall, Rolf Findeisen, Richard D. Braatz, Simon Engelke:
Machine learning benchmarks for the classification of equivalent circuit models from solid-state electrochemical impedance spectra. CoRR abs/2302.03362 (2023) - [i9]Prakitr Srisuma, George Barbastathis, Richard D. Braatz:
Mechanistic Modeling and Analysis of Thermal Radiation in Conventional, Microwave-assisted, and Hybrid Freeze Drying for Biopharmaceutical Manufacturing. CoRR abs/2308.02104 (2023) - [i8]Joachim Schaeffer, Eric Lenz, William C. Chueh, Martin Z. Bazant, Rolf Findeisen, Richard D. Braatz:
Interpretation of High-Dimensional Linear Regression: Effects of Nullspace and Regularization Demonstrated on Battery Data. CoRR abs/2309.00564 (2023) - 2022
- [j60]Anastasia Nikolakopoulou, Moo Sun Hong, Richard D. Braatz:
Dynamic state feedback controller and observer design for dynamic artificial neural network models. Autom. 146: 110622 (2022) - [j59]Pil Rip Jeon
, Moo Sun Hong, Richard D. Braatz:
Compact neural network modeling of nonlinear dynamical systems via the standard nonlinear operator form. Comput. Chem. Eng. 159: 107674 (2022) - [j58]Pavan K. Inguva, Kaylee C. Schickel, Richard D. Braatz
:
Efficient numerical schemes for population balance models. Comput. Chem. Eng. 162: 107808 (2022) - [j57]Joachim Schaeffer
, Richard D. Braatz
:
Latent Variable Method Demonstrator - software for understanding multivariate data analytics algorithms. Comput. Chem. Eng. 167: 108014 (2022) - [c97]Anastasia Nikolakopoulou, Richard D. Braatz:
Fast Nonlinear Model Predictive Control of Distributed Parameter Systems. ACC 2022: 994-999 - [c96]Marc D. Berliner, Benben Jiang
, Daniel A. Cogswell, Martin Z. Bazant
, Richard D. Braatz:
Fast Charging of Lithium-ion Batteries by Mathematical Reformulation as Mixed Continuous-Discrete Simulation. ACC 2022: 5265-5270 - [i7]Joachim Schaeffer, Richard D. Braatz:
Latent Variable Method Demonstrator - Software for Understanding Multivariate Data Analytics Algorithms. CoRR abs/2205.08132 (2022) - [i6]Pavan K. Inguva, Richard D. Braatz:
Efficient Numerical Schemes for Multidimensional Population Balance Models. CoRR abs/2206.12404 (2022) - 2021
- [j56]Yiming Wan, Dongying E. Shen, Sergio Lucia, Rolf Findeisen, Richard D. Braatz:
Polynomial chaos-based H2 output-feedback control of systems with probabilistic parametric uncertainties. Autom. 131: 109743 (2021) - [j55]Weike Sun, Richard D. Braatz
:
Smart process analytics for predictive modeling. Comput. Chem. Eng. 144: 107134 (2021) - [j54]Richard D. Braatz, Thomas A. Badgwell, Phillip R. Westmoreland
:
Foundations in Process Analytics and Machine Learning (FOPAM). Comput. Chem. Eng. 146: 107225 (2021) - [j53]Moo Sun Hong
, Richard D. Braatz
:
Mechanistic modeling and parameter-adaptive nonlinear model predictive control of a microbioreactor. Comput. Chem. Eng. 147: 107255 (2021) - [j52]Shin Hyuk Kim, Jay H. Lee
, Richard D. Braatz
:
Multi-scale fluid dynamics simulation based on MP-PIC-PBE method for PMMA suspension polymerization. Comput. Chem. Eng. 152: 107391 (2021) - [j51]Jinwoo Park
, Jae Hyun Cho, Richard D. Braatz
:
Mathematical modeling and analysis of microwave-assisted freeze-drying in biopharmaceutical applications. Comput. Chem. Eng. 153: 107412 (2021) - [j50]Hongbo Zhao
, Richard D. Braatz, Martin Z. Bazant
:
Image inversion and uncertainty quantification for constitutive laws of pattern formation. J. Comput. Phys. 436: 110279 (2021) - [c95]Sandra C. Wells, Anastasia Nikolakopoulou, Richard D. Braatz:
State Feedback Control of Discrete-Time Lur'e Systems with Sector-Bounded Slope-Restricted Nonlinearities. ACC 2021: 2382-2387 - [c94]Anastasia Nikolakopoulou, Moo Sun Hong, Richard D. Braatz:
Output Feedback Control and Observer Design for Dynamic Artificial Neural Networks. ACC 2021: 2613-2618 - [c93]Hoang Hai Nguyen, Tim Zieger, Sandra C. Wells, Anastasia Nikolakopoulou, Richard D. Braatz, Rolf Findeisen:
Stability Certificates for Neural Network Learning-based Controllers using Robust Control Theory. ACC 2021: 3564-3569 - [i5]Yiming Wan, Dongying E. Shen, Sergio Lucia, Rolf Findeisen, Richard D. Braatz:
A Polynomial Chaos Approach to Robust H∞ Static Output-Feedback Control with Bounded Truncation Error. CoRR abs/2102.08626 (2021) - 2020
- [j49]Shin Hyuk Kim, Jay H. Lee, Richard D. Braatz
:
Multi-phase particle-in-cell coupled with population balance equation (MP-PIC-PBE) method for multiscale computational fluid dynamics simulation. Comput. Chem. Eng. 134: 106686 (2020) - [j48]Ali Mesbah, Joel A. Paulson, Richard D. Braatz
:
An internal model control design method for failure-tolerant control with multiple objectives. Comput. Chem. Eng. 140: 106955 (2020) - [j47]Weike Sun, Antonio R. C. Paiva, Peng Xu, Anantha Sundaram, Richard D. Braatz
:
Fault detection and identification using Bayesian recurrent neural networks. Comput. Chem. Eng. 141: 106991 (2020) - [j46]Weike Sun, Richard D. Braatz
:
Opportunities in tensorial data analytics for chemical and biological manufacturing processes. Comput. Chem. Eng. 143: 107099 (2020) - [j45]Weike Sun, Richard D. Braatz
:
ALVEN: Algebraic learning via elastic net for static and dynamic nonlinear model identification. Comput. Chem. Eng. 143: 107103 (2020) - [j44]Joel A. Paulson
, Edward A. Buehler, Richard D. Braatz
, Ali Mesbah:
Stochastic model predictive control with joint chance constraints. Int. J. Control 93(1): 126-139 (2020) - [j43]Peter M. Attia
, Aditya Grover, Norman Jin
, Kristen A. Severson, Todor M. Markov, Yang-Hung Liao, Michael H. Chen, Bryan Cheong, Nicholas Perkins, Zi Yang, Patrick K. Herring, Muratahan Aykol, Stephen J. Harris, Richard D. Braatz
, Stefano Ermon, William C. Chueh:
Closed-loop optimization of fast-charging protocols for batteries with machine learning. Nat. 578(7795): 397-402 (2020) - [j42]Patrick K. Herring, Chirranjeevi Balaji Gopal, Muratahan Aykol, Joseph Montoya, Abraham Anapolsky, Peter M. Attia
, William Gent, Jens S. Hummelshøj, Linda Hung
, Ha-Kyung Kwon, Patrick Moore, Daniel Schweigert, Kristen A. Severson, Santosh Suram, Zi Yang, Richard D. Braatz
, Brian D. Storey:
BEEP: A Python library for Battery Evaluation and Early Prediction. SoftwareX 11: 100506 (2020) - [c92]Anastasia Nikolakopoulou
, Matthias von Andrian, Richard D. Braatz
:
Fast Model Predictive Control of Startup of a Compact Modular Reconfigurable System for Continuous-Flow Pharmaceutical Manufacturing. ACC 2020: 2778-2783 - [c91]Matthias von Andrian, Richard D. Braatz
:
Stochastic Dynamic Optimization and Model Predictive Control based on Polynomial Chaos Theory and Symbolic Arithmetic. ACC 2020: 3399-3404 - [c90]Pedro Reyero-Santiago, Carlos Ocampo-Martinez, Richard D. Braatz:
Nonlinear Dynamical Analysis for an Ethanol Steam Reformer: A Singular Distributed Parameter System. CDC 2020: 23-29 - [c89]Anastasia Nikolakopoulou
, Moo Sun Hong, Richard D. Braatz:
Feedback Control of Dynamic Artificial Neural Networks Using Linear Matrix Inequalities. CDC 2020: 2210-2215
2010 – 2019
- 2019
- [j41]Fridolin Röder
, Richard D. Braatz
, Ulrike Krewer
:
Direct coupling of continuum and kinetic Monte Carlo models for multiscale simulation of electrochemical systems. Comput. Chem. Eng. 121: 722-735 (2019) - [j40]Lauren F. I. Farias, Jeferson A. Souza
, Richard D. Braatz
, Cezar A. da Rosa:
Coupling of the population balance equation into a two-phase model for the simulation of combined cooling and antisolvent crystallization using OpenFOAM. Comput. Chem. Eng. 123: 246-256 (2019) - [j39]Gintaras V. Reklaitis, Richard D. Braatz
, Marianthi Ierapetritou:
Special issue on pharmaceutical manufacturing. Comput. Chem. Eng. 129 (2019) - [c88]Matthias von Andrian, Richard D. Braatz
:
Offset-free Input-Output Formulations of Stochastic Model Predictive Control Based on Polynomial Chaos Theory. ACC 2019: 360-365 - [c87]Anastasia Nikolakopoulou
, Matthias von Andrian, Richard D. Braatz
:
Plantwide Control of a Compact Modular Reconfigurable System for Continuous- Flow Pharmaceutical Manufacturing. ACC 2019: 2158-2163 - [i4]Andrea Pozzi, Marcello Torchio, Richard D. Braatz, Davide Martino Raimondo:
Optimal Charging of an Electric Vehicle Battery Pack: A Real-Time Sensitivity-Based MPC approach. CoRR abs/1909.12361 (2019) - [i3]Weike Sun, Antonio R. C. Paiva, Peng Xu, Anantha Sundaram, Richard D. Braatz:
Fault Detection and Identification using Bayesian Recurrent Neural Networks. CoRR abs/1911.04386 (2019) - 2018
- [j38]Moo Sun Hong
, Kristen A. Severson, Mo Jiang
, Amos E. Lu, J. Christopher Love, Richard D. Braatz
:
Challenges and opportunities in biopharmaceutical manufacturing control. Comput. Chem. Eng. 110: 106-114 (2018) - [j37]Qiugang Lu
, Benben Jiang
, R. Bhushan Gopaluni, Philip D. Loewen
, Richard D. Braatz
:
Locality preserving discriminative canonical variate analysis for fault diagnosis. Comput. Chem. Eng. 117: 309-319 (2018) - [j36]Kwang-Ki K. Kim, Ernesto Rios-Patron, Richard D. Braatz
:
Standard representation and unified stability analysis for dynamic artificial neural network models. Neural Networks 98: 251-262 (2018) - [c86]Richard D. Braatz
, Jordan M. Berg, Zongli Lin, Frank Allgöwer:
Welcome to the ACC2018. ACC 2018: 1-5 - [c85]Joel A. Paulson
, Tor Aksel N. Heirung, Richard D. Braatz
, Ali Mesbah:
Closed-Loop Active Fault Diagnosis for Stochastic Linear Systems. ACC 2018: 735-741 - [c84]Yiming Wan, Richard D. Braatz
:
Mixed Polynomial Chaos and Worst-Case Synthesis Approach to Robust Observer based Linear Quadratic Regulation. ACC 2018: 6798-6803 - [c83]Yiming Wan, Dongying E. Shen, Sergio Lucia
, Rolf Findeisen
, Richard D. Braatz
:
Robust Static H∞ Output-Feedback Control Using Polynomial Chaos. ACC 2018: 6804-6809 - [c82]Yiming Wan, Vicenç Puig, Carlos Ocampo-Martinez
, Ye Wang, Richard D. Braatz
:
Probability-Guaranteed Set-Membership State Estimation for Polynomially Uncertain Linear Time-Invariant Systems. CDC 2018: 2291-2296 - 2017
- [j35]Kristen A. Severson, Brinda Monian, J. Christopher Love, Richard D. Braatz
:
A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets. Bioinform. 33(18): 2897-2905 (2017) - [c81]Sergio Lucia
, Marcello Torchio, Davide Martino Raimondo, Reinhardt Klein, Richard D. Braatz
, Rolf Findeisen
:
Towards adaptive health-aware charging of Li-ion batteries: A real-time predictive control approach using first-principles models. ACC 2017: 4717-4722 - [c80]Sergio Lucia
, Joel A. Paulson
, Rolf Findeisen
, Richard D. Braatz
:
On stability of stochastic linear systems via polynomial chaos expansions. ACC 2017: 5089-5094 - [c79]Yiming Wan, Eranda Harinath, Richard D. Braatz
:
A piecewise polynomial chaos approach to stochastic linear quadratic regulation for systems with probabilistic parametric uncertainties. CDC 2017: 505-510 - 2016
- [j34]Kristen A. Severson, Paphonwit Chaiwatanodom, Richard D. Braatz
:
Perspectives on process monitoring of industrial systems. Annu. Rev. Control. 42: 190-200 (2016) - [j33]Lixian Zhang, Songlin Zhuang
, Richard D. Braatz
:
Switched model predictive control of switched linear systems: Feasibility, stability and robustness. Autom. 67: 8-21 (2016) - [j32]Joseph K. Scott
, Davide Martino Raimondo, Giuseppe Roberto Marseglia, Richard D. Braatz
:
Constrained zonotopes: A new tool for set-based estimation and fault detection. Autom. 69: 126-136 (2016) - [j31]Davide Martino Raimondo, Giuseppe Roberto Marseglia, Richard D. Braatz
, Joseph K. Scott
:
Closed-loop input design for guaranteed fault diagnosis using set-valued observers. Autom. 74: 107-117 (2016) - [j30]Hong Jang, Kwang-Ki K. Kim, Richard D. Braatz
, R. Bhushan Gopaluni, Jay H. Lee:
Regularized maximum likelihood estimation of sparse stochastic monomolecular biochemical reaction networks. Comput. Chem. Eng. 90: 111-120 (2016) - [j29]Michael L. Rasche, Mo Jiang
, Richard D. Braatz
:
Mathematical modeling and optimal design of multi-stage slug-flow crystallization. Comput. Chem. Eng. 95: 240-248 (2016) - [j28]Masako Kishida
, Richard D. Braatz
:
On the Analysis of the Eigenvalues of Uncertain Matrices by μ and ν: Applications to Bifurcation Avoidance and Convergence Rates. IEEE Trans. Autom. Control. 61(3): 748-753 (2016) - [c78]Eranda Harinath, Lucas C. Foguth, Joel A. Paulson
, Richard D. Braatz
:
Nonlinear model predictive control using polynomial optimization methods. ACC 2016: 1-6 - [c77]Amos E. Lu, Joel A. Paulson
, Richard D. Braatz
:
pH and conductivity control in an integrated biomanufacturing plant. ACC 2016: 1741-1746 - [c76]Tillmann Muhlpfordt, Joel A. Paulson
, Richard D. Braatz
, Rolf Findeisen
:
Output feedback model predictive control with probabilistic uncertainties for linear systems. ACC 2016: 2035-2040 - [c75]Eranda Harinath, Lucas C. Foguth, Richard D. Braatz
:
A robust dual-mode MPC approach to ensuring critical quality attributes in Quality-by-Design. ACC 2016: 2041-2046 - [c74]Rolf Findeisen
, Martha A. Grover, Christian Wagner, Michael Maiworm
, Ruslan Temirov
, F. Stefan Tautz
, Murti V. Salapaka, Srinivasa M. Salapaka, Richard D. Braatz
, S. O. Reza Moheimani
:
Control on a molecular scale: A perspective. ACC 2016: 3069-3082 - [c73]Joel A. Paulson
, Venkatasailanathan Ramadesigan, Venkat R. Subramanian, Richard D. Braatz
:
Control systems analysis and design of multiscale simulation models. ACC 2016: 3083-3085 - [c72]Eranda Harinath, Lucas C. Foguth, Richard D. Braatz
:
Maximization of ellipsoidal design space for continuous-time systems: A robust optimal control approach. ACC 2016: 3850-3855 - [c71]Marcello Torchio, Carlos Ocampo-Martinez, Lalo Magni, Maria Serra Prat
, Richard D. Braatz
, Davide Martino Raimondo:
Fast Model Predictive Control for hydrogen outflow regulation in Ethanol Steam Reformers. ACC 2016: 5044-5049 - [c70]Marcello Torchio, Lalo Magni, Richard D. Braatz
, Davide Martino Raimondo:
Optimal charging of a Li-ion cell: A hybrid Model Predictive Control approach. CDC 2016: 4053-4058 - [c69]Richard D. Braatz:
Advanced Manufacturing of Biopharmaceuticals. ICINCO (1) 2016: 5 - 2015
- [j27]Benben Jiang
, Xiaoxiang Zhu, Dexian Huang, Joel A. Paulson
, Richard D. Braatz
:
A combined canonical variate analysis and Fisher discriminant analysis (CVA-FDA) approach for fault diagnosis. Comput. Chem. Eng. 77: 1-9 (2015) - [j26]Kristen A. Severson, Jeremy G. VanAntwerp, Venkatesh Natarajan, Chris Antoniou, Jörg Thömmes, Richard D. Braatz
:
Elastic net with Monte Carlo sampling for data-based modeling in biopharmaceutical manufacturing facilities. Comput. Chem. Eng. 80: 30-36 (2015) - [c68]Amos E. Lu, Joel A. Paulson
, Nicholas J. Mozdzierz, Alan Stockdale, Ashlee N. Ford Versypt
, Kerry R. Love, J. Christopher Love, Richard D. Braatz
:
Control systems technology in the advanced manufacturing of biologic drugs. CCA 2015: 1505-1515 - [c67]Eranda Harinath, Lucas C. Foguth, Richard D. Braatz
:
Robust optimal control for the maximization of design space. ACC 2015: 3886-3891 - [c66]Lifang Zhou, Xiaoxiang Zhu, Richard D. Braatz
:
Controlled seeding from multiple micromixers for tailoring the product size distribution in a semi-continuous crystallizer design. ACC 2015: 4295-4300 - [c65]Ali Mesbah, Joel A. Paulson
, Richard Lakerveld
, Richard D. Braatz
:
Plant-wide model predictive control for a continuous pharmaceutical process. ACC 2015: 4301-4307 - [c64]Marcello Torchio, Nicolas A. Wolff, Davide Martino Raimondo, Lalo Magni
, Ulrike Krewer, R. Bhushan Gopaluni, Joel A. Paulson
, Richard D. Braatz
:
Real-time model predictive control for the optimal charging of a lithium-ion battery. ACC 2015: 4536-4541 - [c63]Lucas C. Foguth, Joel A. Paulson
, Richard D. Braatz
, Davide Martino Raimondo:
Fast robust model predictive control of high-dimensional systems. ECC 2015: 2009-2014 - [i2]Joel A. Paulson, Edward A. Buehler, Richard D. Braatz, Ali Mesbah:
Receding-horizon Stochastic Model Predictive Control with Hard Input Constraints and Joint State Chance Constraints. CoRR abs/1506.08471 (2015) - [i1]Kwang Ki Kevin Kim, Richard D. Braatz:
Stability Analysis of Discrete-time Lure Systems with Slope-restricted Odd Monotonic Nonlinearities. CoRR abs/1509.01302 (2015) - 2014
- [j25]Joseph K. Scott
, Rolf Findeisen
, Richard D. Braatz, Davide Martino Raimondo:
Input design for guaranteed fault diagnosis using zonotopes. Autom. 50(6): 1580-1589 (2014) - [j24]Hong Jang, Jay H. Lee, Richard D. Braatz
, Kwang Ki Kevin Kim
:
Fast moving horizon estimation for a two-dimensional distributed parameter system. Comput. Chem. Eng. 63: 159-172 (2014) - [j23]Richard D. Braatz
, Jay H. Lee:
Special issue in Honor of Manfred Morari's 60th Birthday. Comput. Chem. Eng. 70: 1-2 (2014) - [j22]Kwang Ki Kevin Kim
, Sigurd Skogestad, Manfred Morari, Richard D. Braatz
:
Necessary and sufficient conditions for robust reliable control in the presence of model uncertainties and system component failures. Comput. Chem. Eng. 70: 67-77 (2014) - [j21]Kwang Ki Kevin Kim, Richard D. Braatz
:
Computational complexity and related topics of robustness margin calculation using μ theory: A review of theoretical developments. Comput. Chem. Eng. 70: 122-132 (2014) - [j20]Ashlee N. Ford Versypt
, Richard D. Braatz
:
Analysis of finite difference discretization schemes for diffusion in spheres with variable diffusivity. Comput. Chem. Eng. 71: 241-252 (2014) - [j19]Masako Kishida
, Philipp Rumschinski
, Rolf Findeisen
, Richard D. Braatz
:
Efficient Polynomial-Time Outer Bounds on State Trajectories for Uncertain Polynomial Systems Using Skewed Structured Singular Values. IEEE Trans. Autom. Control. 59(11): 3063-3068 (2014) - [c62]Ali Mesbah, Stefan Streif
, Rolf Findeisen
, Richard D. Braatz
:
Stochastic nonlinear model predictive control with probabilistic constraints. ACC 2014: 2413-2419 - [c61]Richard Lakerveld
, Brahim Benyahia
, Patrick L. Heider, Haitao Zhang, Aaron Wolfe, Chris Testa, Sean Ogden, Devin R. Hersey, Salvatore Mascia, James M. B. Evans, Richard D. Braatz
, Paul I. Barton:
The application of an automated plant-wide control strategy for a continuous pharmaceutical pilot plant. ACC 2014: 3512-3517 - [c60]Kwang Ki Kevin Kim, Hong Jang, R. Bhushan Gopaluni, Jay H. Lee, Richard D. Braatz
:
Sparse identification in chemical master equations for monomolecular reaction networks. ACC 2014: 3698-3703 - [c59]Masako Kishida
, Richard D. Braatz
:
Non-existence conditions of local bifurcations for rational systems with structured uncertainties. ACC 2014: 5085-5090 - [c58]Masako Kishida
, Richard D. Braatz
:
Volume maximization of consistent parameter sets for linear fractional models. CDC 2014: 1905-1910 - [c57]Joel A. Paulson
, Ali Mesbah, Stefan Streif
, Rolf Findeisen
, Richard D. Braatz
:
Fast stochastic model predictive control of high-dimensional systems. CDC 2014: 2802-2809 - [c56]Joel A. Paulson
, Davide Martino Raimondo, Rolf Findeisen
, Richard D. Braatz
, Stefan Streif
:
Guaranteed active fault diagnosis for uncertain nonlinear systems. ECC 2014: 926-931 - 2013
- [j18]Zachary W. Ulissi, Michael S. Strano, Richard D. Braatz:
Control of nano and microchemical systems. Comput. Chem. Eng. 51: 149-156 (2013) - [j17]Kwang-Ki K. Kim, Richard D. Braatz:
Generalised polynomial chaos expansion approaches to approximate stochastic model predictive control. Int. J. Control 86(8): 1324-1337 (2013) - [c55]Masako Kishida
, Richard D. Braatz:
Inversion-based output regulation of chemotaxis using a constrained influx of chemical signaling molecules. ACC 2013: 3443-3448 - [c54]Joseph K. Scott
, Rolf Findeisen, Richard D. Braatz, Davide Martino Raimondo:
Design of active inputs for set-based fault diagnosis. ACC 2013: 3561-3566 - [c53]Kwang Ki Kevin Kim, Richard D. Braatz:
Convex relaxation of sequential optimal input design for a class of structured large-scale systems: process gain estimation. ACC 2013: 3906-3911 - [c52]Bharatkumar Suthar, Venkatasailanathan Ramadesigan, Paul W. C. Northrop, R. Bhushan Gopaluni, Shriram Santhanagopalan, Richard D. Braatz, Venkat R. Subramanian:
Optimal control and state estimation of lithium-ion batteries using reformulated models. ACC 2013: 5350-5355 - [c51]Kwang Ki Kevin Kim, Richard D. Braatz:
Robustness analysis of uncertain linear descriptor systems: Unified approaches using gLFTs, LMIs, and μ. ACC 2013: 5857-5862 - [c50]Masako Kishida, Richard D. Braatz:
Quality-by-design by using the skewed spherical structured singular value. ACC 2013: 6673-6678 - [c49]Lixian Zhang, Richard D. Braatz:
On switched MPC of a class of switched linear systems with modal dwell time. CDC 2013: 91-96 - [c48]Ali Mesbah, Masako Kishida
, Richard D. Braatz:
Design of multi-objective failure-tolerant control systems for infinite-dimensional systems. CDC 2013: 3006-3013 - [c47]