What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Statistics
His primary areas of study are Control theory, Control engineering, Model predictive control, Control system and Control theory.
His Adaptive control, Open-loop controller and Robust control study in the realm of Control engineering connects with subjects such as Cascade.
His biological study spans a wide range of topics, including Distributed control system, Stability, Networked control system, Decentralised system and Nonlinear system.
Shaoyuan Li studied Control system and Temperature control that intersect with Inverse.
The Control theory study combines topics in areas such as Fuzzy logic, Mathematical optimization, Cluster analysis and System identification.
His Stability research integrates issues from Control and Lyapunov function.
His most cited work include:
- Nash-optimization enhanced distributed model predictive control applied to the Shell benchmark problem (136 citations)
- Networked model predictive control based on neighbourhood optimization for serially connected large-scale processes (108 citations)
- Technical Communique: A synthesis approach of on-line constrained robust model predictive control (97 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Control theory, Model predictive control, Control theory, Mathematical optimization and Nonlinear system.
Shaoyuan Li combines subjects such as Control engineering and Control with his study of Control theory.
His work in the fields of Control, such as Supervisory control, intersects with other areas such as Supervisor.
His Model predictive control research is multidisciplinary, incorporating perspectives in Data-driven, Microgrid, Lyapunov function and Optimal control.
Shaoyuan Li studies Control theory, focusing on PID controller in particular.
Shaoyuan Li has included themes like Upper and lower bounds and Fuzzy logic in his Mathematical optimization study.
He most often published in these fields:
- Control theory (59.25%)
- Model predictive control (38.34%)
- Control theory (18.23%)
What were the highlights of his more recent work (between 2018-2021)?
- Model predictive control (38.34%)
- Control theory (59.25%)
- Control (10.72%)
In recent papers he was focusing on the following fields of study:
His main research concerns Model predictive control, Control theory, Control, Distributed computing and Distributed model predictive control.
His Model predictive control study incorporates themes from Energy, Microgrid, Lyapunov function and Optimal control.
He connects Control theory with Scale in his study.
His Supervisory control study in the realm of Control interacts with subjects such as Supervisor.
His work deals with themes such as Control reconfiguration and Cyber-physical system, which intersect with Distributed model predictive control.
His Control theory study combines topics in areas such as Optimization problem and Topology.
Between 2018 and 2021, his most popular works were:
- Distributed MPC for Coordinated Energy Efficiency Utilization in Microgrid Systems (23 citations)
- Infinite-step opacity and K-step opacity of stochastic discrete-event systems (22 citations)
- Infinite-step opacity and K-step opacity of stochastic discrete-event systems (22 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Statistics
Shaoyuan Li focuses on Model predictive control, Control theory, Opacity, Control and Supervisory control.
His Model predictive control research includes elements of Control theory, Control, Mahalanobis distance and Energy management.
His Control theory research is multidisciplinary, relying on both Abstraction, Robot and System model.
His work on Stability, Nonlinear system and Lyapunov function as part of general Control theory study is frequently connected to Q-learning, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
Shaoyuan Li focuses mostly in the field of Control, narrowing it down to topics relating to State and, in certain cases, Computational complexity theory.
His research integrates issues of Computer network and Design objective in his study of Supervisory control.
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