Control: A perspective
By K. Åström, P. Arun Raj Kumar. at - Automatisierungstechnik, 2014
326 citations recorded by the source corpus.
Subfields: Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/7224af0174242698049cf0b46a73fdeed6da62f0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Steven L. Brunton
- J. Nathan Kutz
- Joshua L. Proctor
- Ziyang Meng
- Xinlei Yi
- Carlo Fischione
- Chenyang Lu
- Sinem Coleri Ergen
Citations in the corpus
- A review of PID control, tuning methods and applications (2020, background): “James Watt’s developed steam engine and gover-nor in 1769 and it was accepted as a first negative feedback device [1–3].”
- Optimization under Uncertainty in the Era of Big Data and Deep Learning: When Machine Learning Meets Mathematical Programming (2019, background): “stability, robustness to disturbances, and safety) in virtually every area of science and engineering, such as biological systems, social networks, and mechanical systems [191].”
- A survey of distributed optimization (2019, background): “…ubiquitous in practical systems especially multi-agent systems, due to extra time required to get information, limited communication speed, computation time and execution time required to implement the control input ( Aström & Kumar, 2014; Cao et al., 2013; Hespanha, Naghshtabrizi, & Xu, 2007 ).”
- Generalizing Koopman Theory to Allow for Inputs and Control (2016, unknown): “The construction of effective controllers typically relies on relatively few states, a computationally feasible model to implement, and fast solvers to minimize latencies introduced by computing estimates of the system [1].”
- Wireless Network Design for Control Systems: A Survey (2017, background): “For a historical review, see the survey [58].”
- Dynamic Mode Decomposition with Control (2014, background): “In particular, controllers developed on a full system may be computationally prohibitive to implement, introducing unacceptably large latencies [2].”
- Advanced control in factory automation: a survey (2017, methodology): “Model-based control concerns with designing a control system and evaluating its performance in a simulation environment by way of mathematical model(s) of the plant (Åstrom and Kumar 2014).”