J. Paulson

发表

Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning

R. Qin, A. Rather, Yang Xu, 2020, Cell Reports Physical Science.

Model predictive control with active learning under model uncertainty: Why, when, and how

Tor Aksel N. Heirung, A. Mesbah, J. Paulson, 2018, AIChE Journal.

Arbitrary Polynomial Chaos for Uncertainty Propagation of Correlated Random Variables in Dynamic Systems

Joel A. Paulson, Ali Mesbah, Edward A. Buehler, 2017 .

Model Predictive Control with Active Learning under Model Uncertainty : Why , When , and How Tor

A. Mesbah, J. Paulson, Shinje Lee, 2018 .

Computationally efficient integrated design and predictive control of flexible energy systems using multi‐fidelity simulation‐based Bayesian optimization

Naitik A. Choksi, J. Paulson, Farshud Sorourifar, 2021, Optimal Control Applications and Methods.

Lyapunov-based stochastic nonlinear model predictive control: Shaping the state probability distribution functions

Joel A. Paulson, Ali Mesbah, Edward A. Buehler, 2015, 2016 American Control Conference (ACC).

Formal Certification Methods for Automated Vehicle Safety Assessment

G. Rizzoni, Ekim Yurtsever, J. Paulson, 2022, IEEE Transactions on Intelligent Vehicles.

Data-Driven Scenario Optimization for Automated Controller Tuning With Probabilistic Performance Guarantees

Joel A. Paulson, Ali Mesbah, A. Mesbah, 2020, IEEE Control Systems Letters.

Stochastic physics-informed neural ordinary differential equations

A. Mesbah, J. Paulson, Jared O’Leary, 2022, Journal of Computational Physics.

for receding-horizon stochastic model predictive

A. Mesbah, S. Streif, J. Paulson, 2015 .

Lyapunov-based Stochastic Nonlinear Model Predictive Control: Shaping the State Probability Density Functions

Edward A. Buehler, A. Mesbah, J. Paulson, 2015 .

Fusion of Machine Learning and MPC under Uncertainty: What Advances Are on the Horizon?

Angela P. Schoellig, T. A. Badgwell, M. Zeilinger, 2022, 2022 American Control Conference (ACC).

Sustainability and Industry 4.0: Obstacles and Opportunities*

B. Bakshi, J. Paulson, 2022, 2022 American Control Conference (ACC).

Stochastic physics-informed neural ordinary differential equations

A. Mesbah, J. Paulson, Jared O’Leary, 2021, J. Comput. Phys..

Efficient Robust Global Optimization for Simulation-based Problems using Decomposed Gaussian Processes: Application to MPC Calibration

J. Paulson, Farshud Sorourifar, Akshay Kudva, 2022, 2022 American Control Conference (ACC).

An Analytical Solution for Exciton Generation, Reaction, and Diffusion in Nanotube and Nanowire-Based Solar Cells.

R. Braatz, M. Strano, J. Paulson, 2016, The journal of physical chemistry letters.

Ultrasensitive and Selective Detection of SARS-CoV-2 Using Thermotropic Liquid Crystals and Image-Based Machine Learning

R. Qin, Yang Xu, Shuang Song, 2020, Cell Reports Physical Science.

No-Regret Bayesian Optimization with Unknown Equality and Inequality Constraints using Exact Penalty Functions

J. Paulson, Congwen Lu, 2022, IFAC-PapersOnLine.

Model-Based Feedback Control of a kHz-Excited Atmospheric Pressure Plasma Jet

David B. Graves, Joel A. Paulson, Ali Mesbah, 2018, IEEE Transactions on Radiation and Plasma Medical Sciences.

Deep Learning-based Approximate Nonlinear Model Predictive Control with Offset-free Tracking for Embedded Applications

Joel A. Paulson, Ali Mesbah, Kimberly J. Chan, 2021, 2021 American Control Conference (ACC).

Fast approximate learning-based multistage nonlinear model predictive control using Gaussian processes and deep neural networks

Joel A. Paulson, Angelo D. Bonzanini, Ali Mesbah, 2020, Comput. Chem. Eng..

Approximate Closed-Loop Robust Model Predictive Control With Guaranteed Stability and Constraint Satisfaction

Joel A. Paulson, Ali Mesbah, A. Mesbah, 2020, IEEE Control Systems Letters.

Stochastic model predictive control with joint chance constraints

Richard D. Braatz, Joel A. Paulson, Ali Mesbah, 2015, Int. J. Control.

Mixed stochastic-deterministic tube MPC for offset-free tracking in the presence of plant-model mismatch

Joel A. Paulson, Tito L.M. Santos, Ali Mesbah, 2019, Journal of Process Control.

An efficient method for stochastic optimal control with joint chance constraints for nonlinear systems

Joel A. Paulson, Ali Mesbah, A. Mesbah, 2019 .

Stochastic Model Predictive Control with Enlarged Domain of Attraction for Offset-Free Tracking

Joel A. Paulson, Ali Mesbah, Tito L. M. Santos, 2018, 2018 Annual American Control Conference (ACC).

Offset-Free Robust MPC of Systems with Mixed Stochastic and Deterministic Uncertainty

Joel A. Paulson, Ali Mesbah, Lantao Xie, 2017 .

Stochastic model predictive control with joint chance constraints pdf

Richard D. Braatz, Joel A. Paulson, Ali Mesbah, 2015, Int. J. Control.

An Adaptive Correction Scheme for Offset-Free Asymptotic Performance in Deep Learning-based Economic MPC

A. Mesbah, D. Krishnamoorthy, J. Paulson, 2021, IFAC-PapersOnLine.

A Low-complexity Tube Controller using Contractive Invariant Sets

Joel A. Paulson, Ali Mesbah, A. Mesbah, 2020, 2020 59th IEEE Conference on Decision and Control (CDC).

Model Predictive Control of Polynomial Systems

Richard D. Braatz, Eranda Harinath, Joel A. Paulson, 2018, Handbook of Model Predictive Control.

Nonlinear model predictive control using polynomial optimization methods

Richard D. Braatz, Eranda Harinath, Joel A. Paulson, 2016, 2016 American Control Conference (ACC).

Stochastic model predictive control - how does it work?

Joel A. Paulson, Ali Mesbah, Tor Aksel N. Heirung, 2017, Comput. Chem. Eng..

Toward Safe Dose Delivery in Plasma Medicine using Projected Neural Network-based Fast Approximate NMPC

David B. Graves, Joel A. Paulson, Angelo D. Bonzanini, 2020 .

Model Predictive Control of an Integrated Continuous Pharmaceutical Manufacturing Pilot Plant

Richard D. Braatz, Joel A. Paulson, Richard Lakerveld, 2017 .

COBALT: COnstrained Bayesian optimizAtion of computationaLly expensive grey-box models exploiting derivaTive information

J. Paulson, Congwen Lu, 2021, Comput. Chem. Eng..

An internal model control design method for failure-tolerant control with multiple objectives

Richard D. Braatz, Joel A. Paulson, Ali Mesbah, 2020, Comput. Chem. Eng..

Stochastic Physics-Informed Neural Networks (SPINN): A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equations pdf

Joel A. Paulson, Ali Mesbah, Jared O'Leary, 2021, ArXiv.

Control and Systems Theory for Advanced Manufacturing

Richard D. Braatz, Eranda Harinath, Joel A. Paulson, 2018 .

Fast stochastic model predictive control of end-to-end continuous pharmaceutical manufacturing 1 1Financial support from Novartis is acknowledged.

Stefan Streif, Richard D. Braatz, Joel A. Paulson, 2018 .

Nonlinear Model Predictive Control of Systems with Probabilistic Time-invariant Uncertainties*

Richard D. Braatz, Eranda Harinath, Joel A. Paulson, 2015 .

Real-time model predictive control for the optimal charging of a lithium-ion battery

Richard D. Braatz, Marcello Torchio, Ulrike Krewer, 2015, 2015 American Control Conference (ACC).

Automated Vehicle Safety Guarantee, Verification and Certification: A Survey

G. Rizzoni, Ekim Yurtsever, J. Paulson, 2022, ArXiv.

Safe Learning-based Model Predictive Control under State- and Input-dependent Uncertainty using Scenario Trees

Joel A. Paulson, Angelo D. Bonzanini, Ali Mesbah, 2020, 2020 59th IEEE Conference on Decision and Control (CDC).

Control systems technology in the advanced manufacturing of biologic drugs

Richard D. Braatz, Amos E. Lu, Joel A. Paulson, 2015, 2015 IEEE Conference on Control Applications (CCA).

A combined canonical variate analysis and Fisher discriminant analysis (CVA-FDA) approach for fault diagnosis

Richard D. Braatz, Dexian Huang, Joel A. Paulson, 2015, Comput. Chem. Eng..

pH and conductivity control in an integrated biomanufacturing plant

Richard D. Braatz, Amos E. Lu, Joel A. Paulson, 2016, 2016 American Control Conference (ACC).

Closed-Loop Active Fault Diagnosis for Stochastic Linear Systems

Richard D. Braatz, Joel A. Paulson, Ali Mesbah, 2018, 2018 Annual American Control Conference (ACC).

Guaranteed active fault diagnosis for uncertain nonlinear systems

Richard D. Braatz, Stefan Streif, Joel A. Paulson, 2014, 2014 European Control Conference (ECC).

Fast robust model predictive control of high-dimensional systems

Richard D. Braatz, Joel A. Paulson, Lucas C. Foguth, 2015, 2015 European Control Conference (ECC).

Control of self-assembly in micro- and nano-scale systems

Richard D. Braatz, Joel A. Paulson, Ali Mesbah, 2015 .

Deep learning for characterizing the self-assembly of three-dimensional colloidal systems.

Ali Mesbah, Jeetain Mittal, Jared O'Leary, 2020, Soft matter.

Optimal Bayesian experiment design for nonlinear dynamic systems with chance constraints

Joel A. Paulson, Ali Mesbah, Marc Martin-Casas, 2019, Journal of Process Control.

An Adaptive Model Predictive Control Strategy for Nonlinear Distributed Parameter Systems using the Type-2 Takagi–Sugeno Model

Huaicheng Yan, Joel A. Paulson, Mengling Wang, 2015, International Journal of Fuzzy Systems.

An Adaptive Model Predictive Control Strategy for Nonlinear Distributed Parameter Systems using the Type-2 Takagi–Sugeno Model

Huaicheng Yan, H. Shi, J. Paulson, 2015, International Journal of Fuzzy Systems.

Shaping the Closed-Loop Behavior of Nonlinear Systems Under Probabilistic Uncertainty Using Arbitrary Polynomial Chaos

Joel A. Paulson, Ali Mesbah, A. Mesbah, 2018, 2018 IEEE Conference on Decision and Control (CDC).

Control systems analysis and design of multiscale simulation models

Richard D. Braatz, Joel A. Paulson, Venkatasailanathan Ramadesigan, 2016, 2016 American Control Conference (ACC).

Bifunctional Catalysts for Alkaline Oxygen Reduction Reaction via Promotion of Ligand and Ensemble Effects at Ag/MnOx Nanodomains

K. Stevenson, K. Johnston, J. Paulson, 2012 .

No-Regret Constrained Bayesian Optimization of Noisy and Expensive Hybrid Models using Differentiable Quantile Function Approximations

J. Paulson, Congwen Lu, 2023, ArXiv.

Layer number dependence of MoS2 photoconductivity using photocurrent spectral atomic force microscopic imaging.

Qing Hua Wang, R. Braatz, M. Strano, 2015, ACS nano.

Plant-wide model predictive control for a continuous pharmaceutical process

Richard D. Braatz, Richard Lakerveld, Joel A. Paulson, 2015, 2015 American Control Conference (ACC).

Fast stochastic model predictive control of high-dimensional systems

Richard D. Braatz, Stefan Streif, Joel A. Paulson, 2014, 53rd IEEE Conference on Decision and Control.

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Truong X. Nghiem, M. Zeilinger, D. Vrabie, 2023, 2023 American Control Conference (ACC).

On stability of stochastic linear systems via polynomial chaos expansions

Richard D. Braatz, Joel A. Paulson, Rolf Findeisen, 2017, 2017 American Control Conference (ACC).

Fast uncertainty quantification for dynamic flux balance analysis using non-smooth polynomial chaos expansions

Ali Mesbah, Marc Martin-Casas, Joel A Paulson, 2019, PLoS Comput. Biol..

Input Design for Online Fault Diagnosis of Nonlinear Systems with Stochastic Uncertainty

Joel A. Paulson, Ali Mesbah, Marc Martin-Casas, 2017 .

Stability for receding-horizon stochastic model predictive control

Stefan Streif, Joel A. Paulson, Ali Mesbah, 2014, 2015 American Control Conference (ACC).

Efficient Multi-Step Lookahead Bayesian Optimization with Local Search Constraints

J. Paulson, A. Chakrabarty, Farshud Sorourifar, 2022, 2022 IEEE 61st Conference on Decision and Control (CDC).

A Data-Driven Automatic Tuning Method for MPC under Uncertainty using Constrained Bayesian Optimization pdf

Farshud Sorourifar, Joel A. Paulson, Ali Mesbah, 2020, IFAC-PapersOnLine.

No-Regret Constrained Bayesian Optimization of Noisy and Expensive Hybrid Models using Differentiable Quantile Function Approximations

J. Paulson, Congwen Lu, 2023, Journal of Process Control.

Nonlinear Model Predictive Control with Explicit Backoffs for Stochastic Systems under Arbitrary Uncertainty

Joel A. Paulson, Ali Mesbah, A. Mesbah, 2018 .

LSR-BO: Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems

C. Laughman, J. Paulson, A. Chakrabarty, 2023, 2023 American Control Conference (ACC).

A Tutorial on Derivative-Free Policy Learning Methods for Interpretable Controller Representations

A. Mesbah, J. Paulson, Farshud Sorourifar, 2023, 2023 American Control Conference (ACC).

Probabilistically Robust Bayesian Optimization for Data-Driven Design of Arbitrary Controllers with Gaussian Process Emulators

A. Mesbah, J. Paulson, Ketong Shao, 2021, 2021 60th IEEE Conference on Decision and Control (CDC).

A combined canonical variate analysis and Fisher discriminant analysis (CVA-FDA) approach for fault diagnosis

Benben Jiang, J. Paulson, R. D. Braatz, 2015, Comput. Chem. Eng..

Understanding Rapid PET Degradation via Reactive Molecular Dynamics Simulation and Kinetic Modeling.

B. Bakshi, Li‐Chiang Lin, J. Paulson, 2023, The journal of physical chemistry. A.

Accelerating Black-Box Molecular Property Optimization by Adaptively Learning Sparse Subspaces

J. Paulson, Farshud Sorourifar, Thomas Banker, 2024, ArXiv.

Safe Explorative Bayesian Optimization - Towards Personalized Treatments in Plasma Medicine

J. Paulson, Kimberly J. Chan, Ali Mesbah, 2023, 2023 62nd IEEE Conference on Decision and Control (CDC).

Self-Optimizing Vapor Compression Cycles Online With Bayesian Optimization Under Local Search Region Constraints

C. Laughman, J. Paulson, A. Chakrabarty, 2023, Journal of Dynamic Systems, Measurement and Control.

Robust Bayesian optimization for flexibility analysis of expensive simulation-based models with rigorous uncertainty bounds

J. Paulson, Akshay Kudva, Wei-Ting Tang, 2023, Comput. Chem. Eng..

ontrol of self-assembly in micro-and nano-scale systems oel

Mark C. Molaro, R. Braatz, A. Mesbah, 2015 .

Stability for receding-horizon stochastic model predictive control

A. Mesbah, S. Streif, J. Paulson, 2014, 2015 American Control Conference (ACC).

Polynomial Chaos-based Stochastic Model Predictive Control: An Overview and Future Research Directions

Prabhat Kumar Mishra, R. Braatz, J. Paulson, 2024, ArXiv.

BEACON: A Bayesian Optimization Strategy for Novelty Search in Expensive Black-Box Systems

J. Paulson, Wei-Ting Tang, Ankush Chakrabarty, 2024, 2406.03616.