[HTML][HTML] Robot learning towards smart robotic manufacturing: A review

Z Liu, Q Liu, W Xu, L Wang, Z Zhou - Robotics and Computer-Integrated …, 2022 - Elsevier
Robotic equipment has been playing a central role since the proposal of smart
manufacturing. Since the beginning of the first integration of industrial robots into production …

All you need to know about model predictive control for buildings

J Drgoňa, J Arroyo, IC Figueroa, D Blum… - Annual Reviews in …, 2020 - Elsevier
It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …

A review on reinforcement learning: Introduction and applications in industrial process control

R Nian, J Liu, B Huang - Computers & Chemical Engineering, 2020 - Elsevier
In recent years, reinforcement learning (RL) has attracted significant attention from both
industry and academia due to its success in solving some complex problems. This paper …

Data-driven model predictive control with stability and robustness guarantees

J Berberich, J Köhler, MA Müller… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
We propose a robust data-driven model predictive control (MPC) scheme to control linear
time-invariant systems. The scheme uses an implicit model description based on behavioral …

Benchmarking model-based reinforcement learning

T Wang, X Bao, I Clavera, J Hoang, Y Wen… - arxiv preprint arxiv …, 2019 - arxiv.org
Model-based reinforcement learning (MBRL) is widely seen as having the potential to be
significantly more sample efficient than model-free RL. However, research in model-based …

Stochastic model predictive control: An overview and perspectives for future research

A Mesbah - IEEE Control Systems Magazine, 2016 - ieeexplore.ieee.org
Model predictive control (MPC) has demonstrated exceptional success for the high-
performance control of complex systems. The conceptual simplicity of MPC as well as its …

Model predictive control: Recent developments and future promise

DQ Mayne - Automatica, 2014 - Elsevier
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[LIVRE][B] Model predictive control of microgrids

C Bordons, F Garcia-Torres, MA Ridao - 2020 - Springer
Control of microgrids is evolving considerably over the past few years. Microgrids, which are
small-scale power systems with a cluster of loads, distributed generators, and storage units …

Deep reinforcement learning based control for Autonomous Vehicles in CARLA

Ó Pérez-Gil, R Barea, E López-Guillén… - Multimedia Tools and …, 2022 - Springer
Abstract Nowadays, Artificial Intelligence (AI) is growing by leaps and bounds in almost all
fields of technology, and Autonomous Vehicles (AV) research is one more of them. This …

Reference and command governors for systems with constraints: A survey on theory and applications

E Garone, S Di Cairano, I Kolmanovsky - Automatica, 2017 - Elsevier
Reference and command governors are add-on control schemes which enforce state and
control constraints on pre-stabilized systems by modifying, whenever necessary, the …