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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]