Analysis and Testing of Ajax-based Single-page Web Applications. - Ali Mesbah 002 (2009)

Closed-loop performance diagnosis using prediction error identification. - Ali Mesbah 002; Xavier Bombois; Jobert H. A. Ludlage; Paul M. J. Van den Hof (CDC/ECC, 2011)

Iterative Learning Control of supersaturation in batch cooling crystallization. - Marco Forgione; Ali Mesbah 002; Xavier Bombois; Paul M. J. Van den Hof (ACC, 2012)

Batch-to-batch strategies for cooling crystallization. - Marco Forgione; Ali Mesbah 002; Xavier Bombois; Paul M. J. Van den Hof (CDC, 2012)

A unified experiment design framework for detection and identification in closed-loop performance diagnosis. - Ali Mesbah 002; Xavier Bombois; Marco Forgione; Jobert H. A. Ludlage; Per Erik Modén; Håkan Hjalmarsson; Paul M. J. Van den Hof (CDC, 2012)

Nonlinear Model-Based Control of a Semi-Industrial Batch Crystallizer Using a Population Balance Modeling Framework. - Ali Mesbah 002; Zoltán K. Nagy; Adrie E. M. Huesman; Herman J. M. Kramer; Paul M. J. Van den Hof (IEEE Trans. Control. Syst. Technol., 2012)

Design of multi-objective failure-tolerant control systems for infinite-dimensional systems. - Ali Mesbah 002; Masako Kishida; Richard D. Braatz (CDC, 2013)

Design of multi-objective control systems with optimal failure tolerance. - Ali Mesbah 002; Richard D. Braatz (ECC, 2013)

Perspectives of data-driven LPV modeling of high-purity distillation columns. - A. A. Bachnas; Roland Tóth; Ali Mesbah 002; Jobert H. A. Ludlage (ECC, 2013)

Model predictive control with integrated experiment design for output error systems. - Christian A. Larsson; Mariette Annergren; Håkan Hjalmarsson; Cristian R. Rojas; Xavier Bombois; Ali Mesbah 002; Per Erik Modén (ECC, 2013)

Stochastic nonlinear model predictive control with probabilistic constraints. - Ali Mesbah 002; Stefan Streif; Rolf Findeisen; Richard D. Braatz (ACC, 2014)

Fast stochastic model predictive control of high-dimensional systems. - Joel A. Paulson; Ali Mesbah 002; Stefan Streif; Rolf Findeisen; Richard D. Braatz (CDC, 2014)

Stability for Receding-horizon Stochastic Model Predictive Control with Chance Constraints. - Ali Mesbah 002; Stefan Streif (CoRR, 2014)

A Probabilistic Approach to Robust Optimal Experiment Design with Chance Constraints. - Ali Mesbah 002; Stefan Streif (CoRR, 2014)

Stochastic Nonlinear Model Predictive Control with Efficient Sample Approximation of Chance Constraints. - Stefan Streif; Matthias Karl; Ali Mesbah 002 (CoRR, 2014)

Plant-wide model predictive control for a continuous pharmaceutical process. - Ali Mesbah 002; Joel A. Paulson; Richard Lakerveld; Richard D. Braatz (ACC, 2015)

Stability for receding-horizon stochastic model predictive control. - Joel A. Paulson; Stefan Streif; Ali Mesbah 002 (ACC, 2015)

Lyapunov-based Stochastic Nonlinear Model Predictive Control: Shaping the State Probability Density Functions. - Edward A. Buehler; Joel A. Paulson; Ali Akhavan; Ali Mesbah 002 (CoRR, 2015)

Receding-horizon Stochastic Model Predictive Control with Hard Input Constraints and Joint State Chance Constraints. - Joel A. Paulson; Edward A. Buehler; Richard D. Braatz; Ali Mesbah 002 (CoRR, 2015)

Least costly closed-loop performance diagnosis and plant re-identification. - Ali Mesbah 002; Xavier Bombois; Marco Forgione; Håkan Hjalmarsson; Paul M. J. Van den Hof (Int. J. Control, 2015)

A polynomial chaos-based nonlinear Bayesian approach for estimating state and parameter probability distribution functions. - Vinay A. Bavdekar; Ali Mesbah 002 (ACC, 2016)

Lyapunov-based stochastic nonlinear model predictive control: Shaping the state probability distribution functions. - Edward A. Buehler; Joel A. Paulson; Ali Mesbah 002 (ACC, 2016)

Model predictive control of thermal effects of an atmospheric pressure plasma jet for biomedical applications. - Dogan Gidon; David B. Graves; Ali Mesbah 002 (ACC, 2016)

Stochastic predictive control with adaptive model maintenance. - Vinay A. Bavdekar; Victoria Ehlinger; Dogan Gidon; Ali Mesbah 002 (CDC, 2016)

A probabilistic framework for reference design for guaranteed fault diagnosis under closed-loop control. - Giuseppe Roberto Marseglia; Davide Martino Raimondo; Lalo Magni; Ali Mesbah 002 (CDC, 2017)

Closed-Loop Active Fault Diagnosis for Stochastic Linear Systems. - Joel A. Paulson; Tor Aksel N. Heirung; Richard D. Braatz; Ali Mesbah 002 (ACC, 2018)

Stochastic Model Predictive Control with Enlarged Domain of Attraction for Offset-Free Tracking. - Tito L. M. Santos; Joel A. Paulson; Ali Mesbah 002 (ACC, 2018)

Shaping the Closed-Loop Behavior of Nonlinear Systems Under Probabilistic Uncertainty Using Arbitrary Polynomial Chaos. - Joel A. Paulson; Ali Mesbah 002 (CDC, 2018)

Stochastic model predictive control with active uncertainty learning: A Survey on dual control. - Ali Mesbah 002 (Annu. Rev. Control., 2018)

Stochastic model predictive control - how does it work? - Tor Aksel N. Heirung; Joel A. Paulson; Jared O'Leary; Ali Mesbah 002 (Comput. Chem. Eng., 2018)

Fault-Tolerant Tube-Based Robust Nonlinear Model Predictive Control. - Joel A. Paulson; Tor Aksel N. Heirung; Ali Mesbah 002 (ACC, 2019)

A Constraint-Tightening Approach to Nonlinear Model Predictive Control with Chance Constraints for Stochastic Systems. - Tito L. M. Santos; Angelo D. Bonzanini; Tor Aksel N. Heirung; Ali Mesbah 002 (ACC, 2019)

Input design for active fault diagnosis. - Tor Aksel N. Heirung; Ali Mesbah 002 (Annu. Rev. Control., 2019)

Model predictive control with active learning for stochastic systems with structural model uncertainty: Online model discrimination. - Tor Aksel N. Heirung; Tito L. M. Santos; Ali Mesbah 002 (Comput. Chem. Eng., 2019)

Fast uncertainty quantification for dynamic flux balance analysis using non-smooth polynomial chaos expansions. - Joel A. Paulson; Marc Martin-Casas; Ali Mesbah 002 (PLoS Comput. Biol., 2019)

Safe Learning-based Model Predictive Control under State- and Input-dependent Uncertainty using Scenario Trees. - Angelo D. Bonzanini; Joel A. Paulson; Ali Mesbah 002 (CDC, 2020)

A Low-complexity Tube Controller using Contractive Invariant Sets. - Joel A. Paulson; Ali Mesbah 002 (CDC, 2020)

Tractable Global Solutions to Bayesian Optimal Experiment Design. - Diogo Rodrigues; Georgios Makrygiorgos; Ali Mesbah 002 (CDC, 2020)

Learning-based Stochastic Model Predictive Control with State-Dependent Uncertainty. - Angelo Domenico Bonzanini; Ali Mesbah 002 (L4DC, 2020)

Stability analysis and stabilization of discrete-time non-homogeneous semi-Markov jump linear systems: A polytopic approach. - Zepeng Ning; Lixian Zhang; Ali Mesbah 002; Patrizio Colaneri (Autom., 2020)

Surrogate modeling for fast uncertainty quantification: Application to 2D population balance models. - Georgios Makrygiorgos; Giovanni Maria Maggioni; Ali Mesbah 002 (Comput. Chem. Eng., 2020)

An internal model control design method for failure-tolerant control with multiple objectives. - Ali Mesbah 002; Joel A. Paulson; Richard D. Braatz (Comput. Chem. Eng., 2020)

PoCET: a Polynomial Chaos Expansion Toolbox for Matlab. - Felix Petzke; Ali Mesbah 002; Stefan Streif (CoRR, 2020)

A Data-Driven Automatic Tuning Method for MPC under Uncertainty using Constrained Bayesian Optimization. - Farshud Sorourifar; Georgios Makrygirgos; Ali Mesbah 002; Joel A. Paulson (CoRR, 2020)

Approximate Closed-Loop Robust Model Predictive Control With Guaranteed Stability and Constraint Satisfaction. - Joel A. Paulson; Ali Mesbah 002 (IEEE Control. Syst. Lett., 2020)

Stochastic model predictive control with joint chance constraints. - Joel A. Paulson; Edward A. Buehler; Richard D. Braatz; Ali Mesbah 002 (Int. J. Control, 2020)

Perception-Aware Chance-Constrained Model Predictive Control for Uncertain Environments. - Angelo D. Bonzanini; Ali Mesbah 002; Stefano Di Cairano (ACC, 2021)

Deep Learning-based Approximate Nonlinear Model Predictive Control with Offset-free Tracking for Embedded Applications. - Kimberly J. Chan; Joel A. Paulson; Ali Mesbah 002 (ACC, 2021)

On the Stability Properties of Perception-aware Chance-constrained MPC in Uncertain Environments. - Angelo D. Bonzanini; Ali Mesbah 002; Stefano Di Cairano (CDC, 2021)

Probabilistically Robust Bayesian Optimization for Data-Driven Design of Arbitrary Controllers with Gaussian Process Emulators. - Joel A. Paulson; Ketong Shao; Ali Mesbah 002 (CDC, 2021)

Fast approximate learning-based multistage nonlinear model predictive control using Gaussian processes and deep neural networks. - Angelo D. Bonzanini; Joel A. Paulson; Georgios Makrygiorgos; Ali Mesbah 002 (Comput. Chem. Eng., 2021)

Stochastic Physics-Informed Neural Networks (SPINN): A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equations. - Jared O'Leary; Joel A. Paulson; Ali Mesbah 002 (CoRR, 2021)

Data-Driven Scenario Optimization for Automated Controller Tuning With Probabilistic Performance Guarantees. - Joel A. Paulson; Ali Mesbah 002 (IEEE Control. Syst. Lett., 2021)

Observation for Markov Jump Piecewise-Affine Systems With Admissible Region-Switching Paths. - Zepeng Ning; Lixian Zhang; Gang Feng 001; Ali Mesbah 002 (IEEE Trans. Autom. Control., 2021)

Learning-based Adaptive-Scenario-Tree Model Predictive Control with Probabilistic Safety Guarantees Using Bayesian Neural Networks. - Yajie Bao; Kimberly J. Chan; Ali Mesbah 002; Javad Mohammadpour Velni (ACC, 2022)

Multi-stage Perception-aware Chance-constrained MPC with Applications to Automated Driving. - Angelo D. Bonzanini; Ali Mesbah 002; Stefano Di Cairano (ACC, 2022)

Fusion of Machine Learning and MPC under Uncertainty: What Advances Are on the Horizon? - Ali Mesbah 002; Kim Peter Wabersich; Angela P. Schoellig; Melanie N. Zeilinger; Sergio Lucia; Thomas A. Badgwell; Joel A. Paulson (ACC, 2022)

Scalable Estimation of Invariant Sets for Mixed-Integer Nonlinear Systems using Active Deep Learning. - Angelo D. Bonzanini; Joel A. Paulson; Georgios Makrygiorgos; Ali Mesbah 002 (CDC, 2022)

Performance-oriented model learning for control via multi-objective Bayesian optimization. - Georgios Makrygiorgos; Angelo D. Bonzanini; Victor Miller; Ali Mesbah 002 (Comput. Chem. Eng., 2022)

Stochastic physics-informed neural ordinary differential equations. - Jared O'Leary; Joel A. Paulson; Ali Mesbah 002 (J. Comput. Phys., 2022)

Efficient Global Solutions to Single-Input Optimal Control Problems via Approximation by Sum-of-Squares Polynomials. - Diogo Rodrigues; Ali Mesbah 002 (IEEE Trans. Autom. Control., 2022)

Learning-Based SMPC for Reference Tracking Under State-Dependent Uncertainty: An Application to Atmospheric Pressure Plasma Jets for Plasma Medicine. - Angelo D. Bonzanini; David B. Graves; Ali Mesbah 002 (IEEE Trans. Control. Syst. Technol., 2022)

Towards Personalized Plasma Medicine via Data-Efficient Adaptation of Fast Deep Learning-based MPC Policies. - Kimberly J. Chan; Georgios Makrygiorgos; Ali Mesbah 002 (ACC, 2023)

A Physics-informed Deep Learning Approach for Minimum Effort Stochastic Control of Colloidal Self-Assembly. - Iman Nodozi; Jared O'Leary; Ali Mesbah 002; Abhishek Halder (ACC, 2023)

Novelty Search for Neuroevolutionary Reinforcement Learning of Deceptive Systems: An Application to Control of Colloidal Self-assembly. - Jared O'Leary; Mira M. Khare; Ali Mesbah 002 (ACC, 2023)

A Tutorial on Derivative-Free Policy Learning Methods for Interpretable Controller Representations. - Joel A. Paulson; Farshud Sorourifar; Ali Mesbah 002 (ACC, 2023)

Safe Explorative Bayesian Optimization - Towards Personalized Treatments in Plasma Medicine. - Kimberly J. Chan; Joel A. Paulson; Ali Mesbah 002 (CDC, 2023)

No-Regret Bayesian Optimization with Gradients Using Local Optimality-Based Constraints: Application to Closed-Loop Policy Search. - Georgios Makrygiorgos; Joel A. Paulson; Ali Mesbah 002 (CDC, 2023)

Traffic Congestion Control Using Distributed Extremum Seeking and Filtered Feedback Linearization Control Approaches. - Pouria Karimi Shahri; Baisravan HomChaudhuri; Srinivas S. Pulugurtha; Ali Mesbah 002; Amir H. Ghasemi (IEEE Control. Syst. Lett., 2023)

Data-Driven Adaptive Optimal Control Under Model Uncertainty: An Application to Cold Atmospheric Plasmas. - Diogo Rodrigues; Kimberly J. Chan; Ali Mesbah 002 (IEEE Trans. Control. Syst. Technol., 2023)

Safe Exploration and Escape Local Minima With Model Predictive Control Under Partially Unknown Constraints. - Raffaele Soloperto; Ali Mesbah 002; Frank Allgöwer (IEEE Trans. Autom. Control., 2023)

Imitation Learning of MPC with Neural Networks: Error Guarantees and Sparsification. - Hendrik Alsmeier; Lukas Theiner; Anton Savchenko; Ali Mesbah 002; Rolf Findeisen (CDC, 2024)

Run-indexed time-varying Bayesian optimization with positional encoding for auto-tuning of controllers: Application to a plasma-assisted deposition process with run-to-run drifts. - Kwanghyun Cho; Ketong Shao; Ali Mesbah 002 (Comput. Chem. Eng., 2024)

Stability-informed Bayesian Optimization for MPC Cost Function Learning. - Sebastian Hirt; Maik Pfefferkorn; Ali Mesbah 002; Rolf Findeisen (CoRR, 2024)

Low-cost sensors and circuits for plasma education: characterizing power and illuminance. - Alessandro N. Vargas; Victor Miller; Ali Mesbah 002; Gabriele Neretti (CoRR, 2024)

Lyapunov Neural ODE Feedback Control Policies. - Joshua Hang Sai Ip; Georgios Makrygiorgos; Ali Mesbah 002 (CoRR, 2024)

Coactive Preference-Guided Multi-Objective Bayesian Optimization: An Application to Policy Learning in Personalized Plasma Medicine. - Ketong Shao; Ankush Chakrabarty; Ali Mesbah 002; Diego Romeres (IEEE Control. Syst. Lett., 2024)

Perception-aware model predictive control for constrained control in unknown environments. - Angelo D. Bonzanini; Ali Mesbah 002; Stefano Di Cairano (Autom., 2024)

Machine learning in process systems engineering: Challenges and opportunities. - Prodromos Daoutidis; Jay H. Lee; Srinivas Rangarajan; Leo Chiang; R. Bhushan Gopaluni; Artur M. Schweidtmann; Iiro Harjunkoski; Mehmet Mercangöz; Ali Mesbah 002; Fani Boukouvala; Fernando V. Lima; Ehecatl Antonio del Rio-Chanona; et al. (Comput. Chem. Eng., 2024)

Neural Schrödinger Bridge With Sinkhorn Losses: Application to Data-Driven Minimum Effort Control of Colloidal Self-Assembly. - Iman Nodozi; Charlie Yan; Mira M. Khare; Abhishek Halder; Ali Mesbah 002 (IEEE Trans. Control. Syst. Technol., 2024)

A Practical Multiobjective Learning Framework for Optimal Hardware-Software Co-Design of Control-on-a-Chip Systems. - Kimberly J. Chan; Joel A. Paulson; Ali Mesbah 002 (IEEE Trans. Control. Syst. Technol., 2024)

User Preference Meets Pareto-Optimality in Multi-Objective Bayesian Optimization. - Joshua Hang Sai Ip; Ankush Chakrabarty; Ali Mesbah 002; Diego Romeres (AAAI, 2025)

Local-Global Learning of Interpretable Control Policies: The Interface between MPC and Reinforcement Learning. - Thomas Banker; Nathan P. Lawrence; Ali Mesbah 002 (ACC, 2025)

User-Preference Meets Pareto-Optimality: Multi-Objective Bayesian Optimization with Local Gradient Search. - Joshua Hang Sai Ip; Ankush Chakrabarty; Ali Mesbah 002; Diego Romeres (CoRR, 2025)

A view on learning robust goal-conditioned value functions: Interplay between RL and MPC. - Nathan P. Lawrence; Philip D. Loewen; Michael G. Forbes; R. Bhushan Gopaluni; Ali Mesbah 002 (CoRR, 2025)

MPCritic: A plug-and-play MPC architecture for reinforcement learning. - Nathan P. Lawrence; Thomas Banker; Ali Mesbah 002 (CoRR, 2025)

Towards Scalable Bayesian Optimization via Gradient-Informed Bayesian Neural Networks. - Georgios Makrygiorgos; Joshua Hang Sai Ip; Ali Mesbah 002 (CoRR, 2025)

Model-free Reinforcement Learning for Model-based Control: Towards Safe, Interpretable and Sample-efficient Agents. - Thomas Banker; Ali Mesbah 002 (CoRR, 2025)