Artemiy Oleinikov, Sergey Soltan, Zarema Balgabekova, Alberto Bemporad & Matteo Rubagotti. (2024) Scenario-based model predictive control with probabilistic human predictions for human–robot coexistence. Control Engineering Practice 142, pages 105769.
Crossref
Alberto Olivares & Ernesto Staffetti. (2023) A statistical moment-based spectral approach to the chance-constrained stochastic optimal control of epidemic models. Chaos, Solitons & Fractals 172, pages 113560.
Crossref
Daniel Landgraf, Andreas Völz, Felix Berkel, Kevin Schmidt, Thomas Specker & Knut Graichen. (2023) Probabilistic prediction methods for nonlinear systems with application to stochastic model predictive control. Annual Reviews in Control 56, pages 100905.
Crossref
Sebastian Curi, Armin Lederer, Sandra Hirche & Andreas Krause. (2022) Safe Reinforcement Learning via Confidence-Based Filters. Safe Reinforcement Learning via Confidence-Based Filters.
Rajnish Bhusal, Diganta Bhattacharjee & Kamesh Subbarao. (2022) Stochastic Model Predictive Control of Discrete-time Cooperative Unmanned System. Stochastic Model Predictive Control of Discrete-time Cooperative Unmanned System.
Yuichiro Aoyama, Augustinos D. Saravanos & Evangelos A. Theodorou. (2021) Receding Horizon Differential Dynamic Programming Under Parametric Uncertainty. Receding Horizon Differential Dynamic Programming Under Parametric Uncertainty.
Hyun-Kyu Choi, Sang Hwan Son & Joseph Sang-Il Kwon. (2021) Inferential Model Predictive Control of Continuous Pulping under Grade Transition. Industrial & Engineering Chemistry Research 60:9, pages 3699-3710.
Crossref
Lilli Frison & Christian Kirches. (2021) Convergence Analysis and Adaptive Order Selection for the Polynomial Chaos Approach to Direct Optimal Control under Uncertainties. SIAM Journal on Control and Optimization 59:1, pages 509-533.
Crossref
P. Petsagkourakis, I.O. Sandoval, E. Bradford, D. Zhang & E.A. del Rio-Chanona. (2020) Reinforcement learning for batch bioprocess optimization. Computers & Chemical Engineering 133, pages 106649.
Crossref
Giacomo Sevieri, Marco Andreini, Anna De Falco & Hermann G. Matthies. (2019) Concrete gravity dams model parameters updating using static measurements. Engineering Structures 196, pages 109231.
Crossref
Xiangzhong Xie & René Schenkendorf. (2019) Stochastic back-off-based robust process design for continuous crystallization of ibuprofen. Computers & Chemical Engineering 124, pages 80-92.
Crossref
Chettapong Janya-anurak, Thomas Bernard & Jürgen Beyerer. (2019) Uncertainty quantification of nonlinear distributed parameter systems using generalized polynomial chaos. at - Automatisierungstechnik 67:4, pages 283-303.
Crossref
Kevin McCarthy & Galen R. Jackson. Risk Assessment of Fuel Property Variability Using Quasi-Random Sampling/Design of Experiments Methodologies. Risk Assessment of Fuel Property Variability Using Quasi-Random Sampling/Design of Experiments Methodologies.
Victor N. Emenike, Xiangzhong Xie, René Schenkendorf, Antje C. Spiess & Ulrike Krewer. (2019) Robust dynamic optimization of enzyme-catalyzed carboligation: A point estimate-based back-off approach. Computers & Chemical Engineering 121, pages 232-247.
Crossref
Ali Mesbah, Ilya V. Kolmanovsky & Stefano Di Cairano. 2019. Handbook of Model Predictive Control. Handbook of Model Predictive Control
75
97
.
Lilli Bergner & Christian Kirches. (2017) The polynomial chaos approach for reachable set propagation with application to chance‐constrained nonlinear optimal control under parametric uncertainties. Optimal Control Applications and Methods 39:2, pages 471-488.
Crossref
Souransu Nandi & Tarunraj Singh. (2018) Chance Constraint based Design of Open-Loop Controllers for Linear Uncertain Systems. IEEE/ASME Transactions on Mechatronics, pages 1-1.
Crossref
Tillmann Muhlpfordt, Rolf Findeisen, Veit Hagenmeyer & Timm Faulwasser. (2018) Comments on Truncation Errors for Polynomial Chaos Expansions. IEEE Control Systems Letters 2:1, pages 169-174.
Crossref
Joel A. Paulson, Eranda Harinath, Lucas C. Foguth & Richard D. Braatz. 2018. Emerging Applications of Control and Systems Theory. Emerging Applications of Control and Systems Theory
63
79
.
Yiming Wan, Eranda Harinath & Richard D. Braatz. (2017) A piecewise polynomial chaos approach to stochastic linear quadratic regulation for systems with probabilistic parametric uncertainties. A piecewise polynomial chaos approach to stochastic linear quadratic regulation for systems with probabilistic parametric uncertainties.
Ali Mesbah. (2016) Stochastic Model Predictive Control: An Overview and Perspectives for Future Research. IEEE Control Systems 36:6, pages 30-44.
Crossref
Stefan Streif, Kwang-Ki K. Kim, Philipp Rumschinski, Masako Kishida, Dongying Erin Shen, Rolf Findeisen & Richard D. Braatz. (2016) Robustness analysis, prediction, and estimation for uncertain biochemical networks: An overview. Journal of Process Control 42, pages 14-34.
Crossref
M. Núñez & D. G. Vlachos. (2015) Steady state likelihood ratio sensitivity analysis for stiff kinetic Monte Carlo simulations. The Journal of Chemical Physics 142:4.
Crossref
Li Dai, Yuanqing Xia & Yulong Gao. (2015) Distributed Model Predictive Control of Linear Systems with Stochastic Parametric Uncertainties and Coupled Probabilistic Constraints. SIAM Journal on Control and Optimization 53:6, pages 3411-3431.
Crossref
Kwang-Ki K. Kim & Richard D. Braatz. (2013) Computational complexity of robust control: A review of theoretical and algorithmic developments. Computational complexity of robust control: A review of theoretical and algorithmic developments.
Kwang-Ki K. Kim, Dongying Erin Shen, Zoltan K. Nagy & Richard D. Braatz. (2013) Wiener's Polynomial Chaos for the Analysis and Control of Nonlinear Dynamical Systems with Probabilistic Uncertainties [Historical Perspectives]. IEEE Control Systems 33:5, pages 58-67.
Crossref