A review of safe reinforcement learning: Methods, theory and applications
Reinforcement Learning (RL) has achieved tremendous success in many complex decision-
making tasks. However, safety concerns are raised during deploying RL in real-world …
making tasks. However, safety concerns are raised during deploying RL in real-world …
Review on model predictive control: An engineering perspective
Abstract Model-based predictive control (MPC) describes a set of advanced control
methods, which make use of a process model to predict the future behavior of the controlled …
methods, which make use of a process model to predict the future behavior of the controlled …
[PDF][PDF] 模型预测控制——现状与挑战
席裕庚， 李德伟， 林姝 - 自动化学报, 2013 - aas.net.cn
摘要30 多年来, 模型预测控制(Model predictive control, MPC) 的理论和技术得到了长足的发展,
但面对经济社会迅速发展对约束优化控制提出的不断增长的要求, 现有的模型预测控制理论和 …
但面对经济社会迅速发展对约束优化控制提出的不断增长的要求, 现有的模型预测控制理论和 …
Model predictive control of power electronic systems: Methods, results, and challenges
Model predictive control (MPC) has established itself as a promising control methodology in
power electronics. This survey paper highlights the most relevant MPC techniques for power …
power electronics. This survey paper highlights the most relevant MPC techniques for power …
Learning-based model predictive control: Toward safe learning in control
Recent successes in the field of machine learning, as well as the availability of increased
sensing and computational capabilities in modern control systems, have led to a growing …
sensing and computational capabilities in modern control systems, have led to a growing …
The safety filter: A unified view of safety-critical control in autonomous systems
Recent years have seen significant progress in the realm of robot autonomy, accompanied
by the expanding reach of robotic technologies. However, the emergence of new …
by the expanding reach of robotic technologies. However, the emergence of new …
[图书][B] Control systems and reinforcement learning
S Meyn - 2022 - books.google.com
A high school student can create deep Q-learning code to control her robot, without any
understanding of the meaning of'deep'or'Q', or why the code sometimes fails. This book is …
understanding of the meaning of'deep'or'Q', or why the code sometimes fails. This book is …
Data-driven model predictive control with stability and robustness guarantees
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 …
time-invariant systems. The scheme uses an implicit model description based on behavioral …
A tutorial review of neural network modeling approaches for model predictive control
An overview of the recent developments of time-series neural network modeling is
presented along with its use in model predictive control (MPC). A tutorial on the construction …
presented along with its use in model predictive control (MPC). A tutorial on the construction …
Energy management schemes, challenges and impacts of emerging inverter technology for renewable energy integration towards grid decarbonization
Carbon emissions are the main cause of air pollution and climate change and demand
immediate and long-term solutions. The provision of effective, cost-effective energy solutions …
immediate and long-term solutions. The provision of effective, cost-effective energy solutions …