What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Control theory
Bruce H. Krogh spends much of his time researching Hybrid system, Algorithm, Control system, Control theory and State space.
The Hybrid system study combines topics in areas such as Model checking, Formal verification, Theoretical computer science, Transition system and Computation.
As part of the same scientific family, Bruce H. Krogh usually focuses on Computation, concentrating on Distributed computing and intersecting with Network dynamics and Application software.
His Control system research is multidisciplinary, relying on both Path, Remotely operated underwater vehicle and Vehicle dynamics.
His Control theory research incorporates themes from State, Model predictive control and Supervisory control.
His study looks at the relationship between Supervisory control and fields such as Discrete system, as well as how they intersect with chemical problems.
His most cited work include:
- Distributed model predictive control (803 citations)
- Energy-efficient surveillance system using wireless sensor networks (650 citations)
- Deadlock avoidance in flexible manufacturing systems with concurrently competing process flows (481 citations)
What are the main themes of his work throughout his whole career to date?
Bruce H. Krogh mainly focuses on Control engineering, Control theory, Control system, Hybrid system and Theoretical computer science.
His studies in Control engineering integrate themes in fields like Real-time computing, Mobile robot and Fault detection and isolation.
His Control theory study incorporates themes from Mathematical optimization, State, Electric power system and Supervisory control.
In his research, Discrete system is intimately related to Petri net, which falls under the overarching field of Supervisory control.
His biological study spans a wide range of topics, including Automation, Systems engineering, Automatic control, Control and Control theory.
His Hybrid system study combines topics from a wide range of disciplines, such as Set, State space and Algorithm, Formal verification, Computation.
He most often published in these fields:
- Control engineering (24.49%)
- Control theory (24.49%)
- Control system (22.45%)
What were the highlights of his more recent work (between 2008-2020)?
- Distributed computing (9.80%)
- Control engineering (24.49%)
- Control theory (24.49%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Distributed computing, Control engineering, Control theory, Cyber-physical system and Theoretical computer science.
Bruce H. Krogh has included themes like Control and Data center in his Distributed computing study.
His work deals with themes such as Electric power system and Reinforcement learning, which intersect with Control engineering.
His work in Control theory addresses subjects such as Formal verification, which are connected to disciplines such as Behavioral modeling.
His study in Cyber-physical system is interdisciplinary in nature, drawing from both Software architecture, Computation, Rotation formalisms in three dimensions and Systems modeling.
His research in Real-time computing intersects with topics in Telecommunications and Wireless sensor network.
Between 2008 and 2020, his most popular works were:
- Wind Integration in Power Systems: Operational Challenges and Possible Solutions (299 citations)
- A Cyber–Physical Systems Approach to Data Center Modeling and Control for Energy Efficiency (127 citations)
- A cyber-physical systems approach to energy management in data centers (76 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Control theory
Bruce H. Krogh focuses on Cyber-physical system, Hybrid system, Distributed computing, Nonlinear system and Control engineering.
His Hybrid system research is under the purview of Control theory.
His study looks at the intersection of Control theory and topics like Bounded function with Formal verification.
His Distributed computing research is multidisciplinary, incorporating elements of Model checking, View model, Embedded system, Computation and Systems architecture.
His Nonlinear system study integrates concerns from other disciplines, such as State variable and State space.
His Control engineering research includes themes of Leverage and Reinforcement learning.
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