2021 - IEEE Fellow For contributions to optimal and model predictive control
His primary areas of investigation include Model predictive control, Control theory, Network packet, Control engineering and Communication channel. His Model predictive control study combines topics from a wide range of disciplines, such as Linear system, Converters, Power control, Control theory and Power electronics. His biological study spans a wide range of topics, including Quantization, Capacitor, Inverter, Optimization problem and Electronic engineering.
His Network packet research includes themes of Control system, Networked control system, Real-time computing, Bounded function and Robustness. His work deals with themes such as Digital control and Actuator, which intersect with Control engineering. His Communication channel research incorporates themes from Kalman filter, Markov chain, Data transmission and Wireless.
His primary areas of study are Control theory, Model predictive control, Network packet, Control system and Control theory. His Control theory study incorporates themes from Converters, Mathematical optimization and Communication channel. His studies examine the connections between Communication channel and genetics, as well as such issues in Wireless, with regards to Wireless sensor network, Power control, Transmission, Real-time computing and Computer network.
His Model predictive control research is multidisciplinary, incorporating elements of Linear system, Control engineering, Power electronics, Optimization problem and Robustness. His research investigates the connection between Network packet and topics such as Covariance that intersect with issues in State. His research in Control system intersects with topics in Quantization, Distributed computing, Optimal control, Actuator and Scheduling.
Control system, Mathematical optimization, Control theory, Scheduling and Estimator are his primary areas of study. His Control system research is multidisciplinary, relying on both Stability, Sliding mode control, Control theory and Distributed computing. His studies in Mathematical optimization integrate themes in fields like Algorithm design, Communication channel and Encryption.
His work carried out in the field of Control theory brings together such families of science as Bounded function and Model predictive control. His Model predictive control research incorporates elements of Homomorphic encryption, Converters, Interconnection and Robustness. The Scheduling study which covers Wireless that intersects with Wireless sensor network and Real-time computing.
Daniel E. Quevedo mostly deals with Mathematical optimization, Control theory, Scheduling, Control system and Linear system. In his research, Distributed algorithm, Periodic scheduling, Directed graph, Metaheuristic and Exponential stability is intimately related to Algorithm design, which falls under the overarching field of Mathematical optimization. He combines subjects such as Converters, Finite set and Capacitor with his study of Control theory.
His Scheduling research includes elements of Distributed computing, Optimal control and Reinforcement learning. The concepts of his Linear system study are interwoven with issues in Control theory, Stochastic control and Model predictive control. Daniel E. Quevedo interconnects Homomorphic encryption, Encryption, Control channel, Bounded function and Cloud computing in the investigation of issues within Model predictive control.
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Predictive Control in Power Electronics and Drives
P. Cortes;M.P. Kazmierkowski;R.M. Kennel;D.E. Quevedo.
IEEE Transactions on Industrial Electronics (2008)
Predictive Current Control Strategy With Imposed Load Current Spectrum
P. Cortes;J. Rodriguez;D.E. Quevedo;C. Silva.
IEEE Transactions on Power Electronics (2008)
A moving horizon approach to Networked Control system design
G.C. Goodwin;H. Haimovich;D.E. Quevedo;J.S. Welsh.
IEEE Transactions on Automatic Control (2004)
Simple coding for achieving mean square stability over bit-rate limited channels
E.I. Silva;M.S. Derpich;J. Ostergaard;D.E. Quevedo.
conference on decision and control (2008)
Model Predictive Control of an Asymmetric Flying Capacitor Converter
P. Lezana;R. Aguilera;D.E. Quevedo.
IEEE Transactions on Industrial Electronics (2009)
Jamming Attacks on Remote State Estimation in Cyber-Physical Systems: A Game-Theoretic Approach
Yuzhe Li;Ling Shi;Peng Cheng;Jiming Chen.
IEEE Transactions on Automatic Control (2015)
Predictive Optimal Switching Sequence Direct Power Control for Grid-Connected Power Converters
Sergio Vazquez;Abraham Marquez;Ricardo Aguilera;Daniel Quevedo.
IEEE Transactions on Industrial Electronics (2015)
Multistep Finite Control Set Model Predictive Control for Power Electronics
Tobias Geyer;Daniel E. Quevedo.
IEEE Transactions on Power Electronics (2014)
Model Predictive Control of an AFE Rectifier With Dynamic References
D. E. Quevedo;R. P. Aguilera;M. A. Perez;P. Cortes.
IEEE Transactions on Power Electronics (2012)
Performance of Multistep Finite Control Set Model Predictive Control for Power Electronics
Tobias Geyer;Daniel E. Quevedo.
IEEE Transactions on Power Electronics (2015)
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