Stability Analysis of Piecewise Affine Systems with Multi-model Model Predictive Control. - Panagiotis Petsagkourakis; William Paul Heath; Constantinos Theodoropoulos (CoRR, 2018)

Input-Output Stability of Barrier-Based Model Predictive Control. - Panagiotis Petsagkourakis; William Paul Heath; Joaquín Carrasco; Constantinos Theodoropoulos (CoRR, 2019)

Stability analysis of piecewise affine systems with multi-model predictive control. - Panagiotis Petsagkourakis; William Paul Heath; Constantinos Theodoropoulos (Autom., 2020)

Reinforcement learning for batch bioprocess optimization. - Panagiotis Petsagkourakis; Ilya Orson Sandoval; Eric Bradford; Dongda Zhang; Ehecatl Antonio del Rio-Chanona (Comput. Chem. Eng., 2020)

Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty. - Panagiotis Petsagkourakis; Ilya Orson Sandoval; Eric Bradford; Dongda Zhang; Ehecatl Antonio del Rio-Chanona (CoRR, 2020)

Chance Constrained Policy Optimization for Process Control and Optimization. - Panagiotis Petsagkourakis; Ilya Orson Sandoval; Eric Bradford; Federico Galvanin; Dongda Zhang; Ehecatl Antonio del Rio-Chanona (CoRR, 2020)

Modifier Adaptation Meets Bayesian Optimization and Derivative-Free Optimization. - Ehecatl Antonio del Rio-Chanona; Panagiotis Petsagkourakis; Eric Bradford; Jose Eduardo Alves Graciano; Benoît Chachuat (CoRR, 2020)

Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes. - Panagiotis Petsagkourakis; Benoît Chachuat; Ehecatl Antonio del Rio-Chanona (CDC, 2021)

Constrained model-free reinforcement learning for process optimization. - Elton Pan; Panagiotis Petsagkourakis; Max Mowbray; Dongda Zhang; Ehecatl Antonio del Rio-Chanona (Comput. Chem. Eng., 2021)

Safe model-based design of experiments using Gaussian processes. - Panagiotis Petsagkourakis; Federico Galvanin (Comput. Chem. Eng., 2021)

Real-time optimization meets Bayesian optimization and derivative-free optimization: A tale of modifier adaptation. - Ehecatl Antonio del Rio-Chanona; Panagiotis Petsagkourakis; Eric Bradford; Jose Eduardo Alves Graciano; Benoît Chachuat (Comput. Chem. Eng., 2021)

Safe Chance Constrained Reinforcement Learning for Batch Process Control. - Max Mowbray; Panagiotis Petsagkourakis; Ehecatl Antonio del Rio-Chanona; Robin Smith; Dongda Zhang (CoRR, 2021)

Data-driven distributionally robust MPC using the Wasserstein metric. - Zhengang Zhong; Ehecatl Antonio del Rio-Chanona; Panagiotis Petsagkourakis (CoRR, 2021)

Integrating process design and control using reinforcement learning. - Steven Sachio; Max Mowbray; Maria M. Papathanasiou; Ehecatl Antonio del Rio-Chanona; Panagiotis Petsagkourakis (CoRR, 2021)

Robust Stability of Barrier-Based Model Predictive Control. - Panagiotis Petsagkourakis; William Paul Heath; Joaquín Carrasco; Constantinos Theodoropoulos (IEEE Trans. Autom. Control., 2021)

Safe chance constrained reinforcement learning for batch process control. - Max Mowbray; Panagiotis Petsagkourakis; Ehecatl Antonio del Rio-Chanona; Dongda Zhang (Comput. Chem. Eng., 2022)

Neural ODEs as Feedback Policies for Nonlinear Optimal Control. - Ilya Orson Sandoval; Panagiotis Petsagkourakis; Ehecatl Antonio del Rio-Chanona (CoRR, 2022)

An efficient data-driven distributionally robust MPC leveraging linear programming. - Zhengang Zhong; Ehecatl Antonio del Rio-Chanona; Panagiotis Petsagkourakis (ACC, 2023)

Tube-based distributionally robust model predictive control for nonlinear process systems via linearization. - Zhengang Zhong; Ehecatl Antonio del Rio-Chanona; Panagiotis Petsagkourakis (Comput. Chem. Eng., 2023)