Search Results for author: Richard D. Braatz

Found 9 papers, 3 papers with code

An Execution-time-certified QP Algorithm for $\ell_1$ penalty-based Soft-constrained MPC

no code implementations27 Mar 2024 Liang Wu, Richard D. Braatz

Providing an execution time certificate and handling possible infeasibility in closed-loop are two pressing requirements of Model Predictive Control (MPC).

LCEN: A Novel Feature Selection Algorithm for Nonlinear, Interpretable Machine Learning Models

no code implementations27 Feb 2024 Pedro Seber, Richard D. Braatz

Interpretable architectures can have advantages over black-box architectures, and interpretability is essential for the application of machine learning in critical settings, such as aviation or medicine.

feature selection Interpretable Machine Learning

An Execution-time-certified Riccati-based IPM Algorithm for RTI-based Input-constrained NMPC

no code implementations25 Feb 2024 Liang Wu, Krystian Ganko, Shimin Wang, Richard D. Braatz

The execution-time certified capability of the algorithm is theoretically and numerically validated through a case study involving nonlinear control of the chaotic Lorenz system.

Model Predictive Control

Nonparametric Steady-state Learning for Robust Output Regulation of Nonlinear Output Feedback Systems

no code implementations25 Feb 2024 Shimin Wang, Martin Guay, Richard D. Braatz

This article addresses the nonadaptive and robust output regulation problem of the general nonlinear output feedback system with error output.

Interpretation of High-Dimensional Linear Regression: Effects of Nullspace and Regularization Demonstrated on Battery Data

1 code implementation1 Sep 2023 Joachim Schaeffer, Eric Lenz, William C. Chueh, Martin Z. Bazant, Rolf Findeisen, Richard D. Braatz

We developed an optimization formulation to compare regression coefficients and coefficients obtained by physical engineering knowledge to understand which part of the coefficient differences are close to the nullspace.

regression

Dynamics and Control of Oscillatory Bioreactors

1 code implementation27 Jun 2023 Pavan Inguva, Krystian Ganko, Alexis B. Dubs, Richard D. Braatz

Oscillatory dynamical behavior is undesirable as it can impact downstream processes, especially in a continuous operation, and can make process operations and product quality control more challenging.

Extracting particle size distribution from laser speckle with a physics-enhanced autocorrelation-based estimator (PEACE)

no code implementations20 Apr 2022 Qihang Zhang, Janaka C. Gamekkanda, Ajinkya Pandit, Wenlong Tang, Charles Papageorgiou, Chris Mitchell, Yihui Yang, Michael Schwaerzler, Tolutola Oyetunde, Richard D. Braatz, Allan S. Myerson, George Barbastathis

Extracting quantitative information about highly scattering surfaces from an imaging system is challenging because the phase of the scattered light undergoes multiple folds upon propagation, resulting in complex speckle patterns.

BIG-bench Machine Learning

Fault Detection and Identification using Bayesian Recurrent Neural Networks

no code implementations11 Nov 2019 Weike Sun, Antonio R. C. Paiva, Peng Xu, Anantha Sundaram, Richard D. Braatz

In processing and manufacturing industries, there has been a large push to produce higher quality products and ensure maximum efficiency of processes.

Fault Detection

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