Research graph
References from Online adaptive model‐based stochastic control with limited data: A case study with a colloidal self‐assembly system. Local targets link to admitted publications; unresolved targets remain external evidence.
Guided assembly of colloidal particles on patterned substrates
10.1021/la010682j · 2001 · External reference
Assembly of colloidal aggregates by electrohydrodynamic flow: kinetic experiments and scaling analysis
10.1103/physreve.69.021405 · 2004 · External reference
Tunable colloids: control of colloidal phase transitions with tunable interactions
10.1039/b704251p · 2007 · External reference
Interactions and microstructures in electric field mediated colloidal assembly
10.1063/1.3241081 · 2009 · External reference
Control of microparticle assembly
10.1146/annurev-control-042920-100621 · 2022 · External reference
10.23919/acc55779.2023.10156176
10.23919/acc55779.2023.10156176 · External reference
A tutorial review of machine learning‐based model predictive control methods
10.1515/revce-2024-0055 · 2025 · External reference
10.23919/acc55779.2023.10155994
10.23919/acc55779.2023.10155994 · External reference
Unresolved reference
External reference
Reinforcement learning‐based model predictive control for discrete‐time systems
10.1109/tnnls.2023.3273590 · 2024 · External reference
Stochastic model predictive control: an overview and perspectives for future research
10.1109/mcs.2016.2602087 · 2016 · External reference
Unresolved reference
2018 · External reference
Controlling colloidal crystals via morphing energy landscapes and reinforcement learning
10.1126/sciadv.abd6716 · 2020 · External reference
Dynamic control of self‐assembly of quasicrystalline structures through reinforcement learning
10.1039/d4sm01038h · 2025 · External reference
From predictive modelling to machine learning and reverse engineering of colloidal self‐assembly
10.1038/s41563-021-01014-2 · 2021 · External reference
Learning to grow: control of material self‐assembly using evolutionary reinforcement learning
10.1103/physreve.101.052604 · 2020 · External reference
Machine learning‐based optimal control for colloidal self‐assembly
10.1002/aic.70389 · 2026 · External reference
10.3390/pr13061791
10.3390/pr13061791 · External reference
Active control of equilibrium, near‐equilibrium, and far‐from‐equilibrium colloidal systems
10.1039/d2sm01447e · 2023 · External reference
Optimal feedback controlled assembly of perfect crystals
10.1021/acsnano.6b02400 · 2016 · External reference
The construction and application of Markov state models for colloidal self‐assembly process control
10.1039/c6me00092d · 2017 · External reference
Free energy landscapes for colloidal crystal assembly
10.1039/c0sm01526a · 2011 · External reference
Reinforcement learning with model predictive control for highway ramp metering
10.1109/tits.2025.3549227 · 2025 · External reference
Control‐oriented system identification: classical, learning, and physics‐informed approaches
10.1016/j.arcontrol.2026.101067 · 2026 · External reference
Performance‐oriented model learning for data‐driven MPC design
10.1109/lcsys.2019.2913347 · 2019 · External reference
A comparison of open‐loop and closed‐loop strategies in colloidal self‐assembly
10.1016/j.jprocont.2017.06.003 · 2017 · External reference
The cross‐entropy method for combinatorial and continuous optimization
10.1023/a:1010091220143 · 1999 · External reference
Unresolved reference
2013 · External reference
Unresolved reference
2015 · External reference
Unresolved reference
2010 · External reference
Machine learning‐based optimal control for colloidal self‐assembly
10.1002/aic.70389 · ExternalCitation · doi-reference
Control‐oriented system identification: classical, learning, and physics‐informed approaches
10.1016/j.arcontrol.2026.101067 · ExternalCitation · doi-reference
A comparison of open‐loop and closed‐loop strategies in colloidal self‐assembly
10.1016/j.jprocont.2017.06.003 · ExternalCitation · doi-reference
Optimal feedback controlled assembly of perfect crystals
10.1021/acsnano.6b02400 · ExternalCitation · doi-reference
Guided assembly of colloidal particles on patterned substrates
10.1021/la010682j · ExternalCitation · doi-reference
The cross‐entropy method for combinatorial and continuous optimization
10.1023/a:1010091220143 · ExternalCitation · doi-reference
From predictive modelling to machine learning and reverse engineering of colloidal self‐assembly
10.1038/s41563-021-01014-2 · ExternalCitation · doi-reference
Tunable colloids: control of colloidal phase transitions with tunable interactions
10.1039/b704251p · ExternalCitation · doi-reference
Free energy landscapes for colloidal crystal assembly
10.1039/c0sm01526a · ExternalCitation · doi-reference
The construction and application of Markov state models for colloidal self‐assembly process control
10.1039/c6me00092d · ExternalCitation · doi-reference
Active control of equilibrium, near‐equilibrium, and far‐from‐equilibrium colloidal systems
10.1039/d2sm01447e · ExternalCitation · doi-reference
Dynamic control of self‐assembly of quasicrystalline structures through reinforcement learning
10.1039/d4sm01038h · ExternalCitation · doi-reference
Interactions and microstructures in electric field mediated colloidal assembly
10.1063/1.3241081 · ExternalCitation · doi-reference
Learning to grow: control of material self‐assembly using evolutionary reinforcement learning
10.1103/physreve.101.052604 · ExternalCitation · doi-reference
Assembly of colloidal aggregates by electrohydrodynamic flow: kinetic experiments and scaling analysis
10.1103/physreve.69.021405 · ExternalCitation · doi-reference
Performance‐oriented model learning for data‐driven MPC design
10.1109/lcsys.2019.2913347 · ExternalCitation · doi-reference
Stochastic model predictive control: an overview and perspectives for future research
10.1109/mcs.2016.2602087 · ExternalCitation · doi-reference
Reinforcement learning with model predictive control for highway ramp metering
10.1109/tits.2025.3549227 · ExternalCitation · doi-reference
Reinforcement learning‐based model predictive control for discrete‐time systems
10.1109/tnnls.2023.3273590 · ExternalCitation · doi-reference
Controlling colloidal crystals via morphing energy landscapes and reinforcement learning
10.1126/sciadv.abd6716 · ExternalCitation · doi-reference
Control of microparticle assembly
10.1146/annurev-control-042920-100621 · ExternalCitation · doi-reference
A tutorial review of machine learning‐based model predictive control methods
10.1515/revce-2024-0055 · ExternalCitation · doi-reference
10.23919/acc55779.2023.10155994
10.23919/acc55779.2023.10155994 · ExternalCitation · doi-reference
10.23919/acc55779.2023.10156176
10.23919/acc55779.2023.10156176 · ExternalCitation · doi-reference
10.3390/pr13061791
10.3390/pr13061791 · ExternalCitation · doi-reference
